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Showing 1 - 20 of 147 results

Developing Experimental Probabilistic Intensity Forecast Products for Landfalling Tropical Cyclones

Eicher, Robert

;

Halperin, Daniel J.

2025 | Meteorological Applications, 2025; 32:e70089 | PDF

An increasing body of evidence indicates that publics want more probabilistic information included in their weather forecasts. However, more guidance on incorporating probability information into weather risk communication is needed. The National Hurricane Center (NHC) recently developed prototype forecast graphics that include probabilistic values ...

11/14/2025

Supporting Files

Title : Developing Experimental Probabilistic Intensity Forecast Products for Landfalling Tropical Cyclones Personal Author(s) : Eicher, Robert;Halperin, Daniel J.;Trabing, Benjamin C.;Lane, Derek;Sellnow, Deanna;Sellnow, Timothy;Croker, Madison; Published Date : 2025 Source : Meteorological Applications, 2025; 32:e70089 DOI : https://doi.org/10.1002/met.70089 Journal Title : Meteorological Applications Eicher, Robert et al. (2025). Developing Experimental Probabilistic Intensity Forecast Products for Landfalling Tropical Cyclones. 32(4). https://doi.org/10.1002/met.70089 Eicher, Robert et al. "Developing Experimental Probabilistic Intensity Forecast Products for Landfalling Tropical Cyclones" 32, no. 4 (2025), https://doi.org/10.1002/met.70089 Eicher, Robert et al. "Developing Experimental Probabilistic Intensity Forecast Products for Landfalling Tropical Cyclones" vol. 32, no. 4, 2025, https://doi.org/10.1002/met.70089 Export RIS Citation Information. TY - AU - Eicher, Robert AU - Halperin, Daniel J. AU - Trabing, Benjamin C. AU - Lane, Derek AU - Sellnow, Deanna AU - Sellnow, Timothy AU - Croker, Madison AB - An increasing body of evidence indicates that publics want more probabilistic information included in their weather forecasts. However, more guidance on incorporating probability information into weather risk communication is needed. The National Hurricane Center (NHC) recently developed prototype forecast graphics that include probabilistic values of intensity at landfall when landfall is possible. The goal of this research was to develop those prototypes into a forecast product that expresses technical uncertainty in an intensity forecast in a manner that is understandable and effective to various publics. In Study 1, an online survey among Florida residents was conducted. Quantitative analysis of the survey data showed few significant differences between the prototypes and the currently operational forecast track graphic, commonly referred to as the cone of uncertainty (COU). Analysis of the responses to open-ended questions in the survey and feedback from focus group participants consisting of NHC partners working in hurricane-prone areas guided revisions to improve the prototypes. In Study 2, the modified prototypes produced an improvement in understanding of certain aspects of the intensity forecast. Promisingly, most people surveyed preferred the additional probabilistic information in the prototypes to the status quo COU message. In fact, nearly 90% of respondents indicated that they preferred at least some percentage values in their weather forecasts as opposed to forecasts with words only. This suggests that further development of a probabilistic landfall intensity product might be warranted. AN - noaa:71980 DO - https://doi.org/10.1002/met.70089 IS - 4 J2 - Meteorological Applications KW - Cyclones KW - Risk communication KW - Probabilstic forecasting KW - Risk communication KW - Cyclones PY - 2025 T2 - Meteorological Applications T2 - Meteorological Applications, 2025; 32:e70089 TI - Developing Experimental Probabilistic Intensity Forecast Products for Landfalling Tropical Cyclones VL - 32 UR - https://repository.library.noaa.gov/view/noaa/71980 ER -
Public Willingness to Pay for Continuous and Probabilistic Hazard Information

Wehde, Wesley

;

Ripberger, Joseph T.

2021 | Nat. Hazards Rev., 2021, 22(2): 04021004 | PDF

Investments in new weather forecasting technologies and communication products can be costly and serve the ultimate purpose of protecting life and property. The Forecasting a Continuum of Environmental Threats (FACETs) paradigm attempts to improve technology and communication through the provision of probabilistic hazard information (PHI). The rese ...

11/14/2025

Title : Public Willingness to Pay for Continuous and Probabilistic Hazard Information Personal Author(s) : Wehde, Wesley;Ripberger, Joseph T.;Jenkins-Smith, Hank;Jones, Benjamin A.;Allan, Jinan N.;Silva, Carol L.; Published Date : 2021 Source : Nat. Hazards Rev., 2021, 22(2): 04021004 DOI : https://doi.org/10.1061/(ASCE)NH.1527-6996.0000444 Journal Title : Natural Hazards Review Wehde, Wesley et al. (2021). Public Willingness to Pay for Continuous and Probabilistic Hazard Information. 22(2). https://doi.org/10.1061/(ASCE)NH.1527-6996.0000444 Wehde, Wesley et al. "Public Willingness to Pay for Continuous and Probabilistic Hazard Information" 22, no. 2 (2021), https://doi.org/10.1061/(ASCE)NH.1527-6996.0000444 Wehde, Wesley et al. "Public Willingness to Pay for Continuous and Probabilistic Hazard Information" vol. 22, no. 2, 2021, https://doi.org/10.1061/(ASCE)NH.1527-6996.0000444 Export RIS Citation Information. TY - AU - Wehde, Wesley AU - Ripberger, Joseph T. AU - Jenkins-Smith, Hank AU - Jones, Benjamin A. AU - Allan, Jinan N. AU - Silva, Carol L. AB - Investments in new weather forecasting technologies and communication products can be costly and serve the ultimate purpose of protecting life and property. The Forecasting a Continuum of Environmental Threats (FACETs) paradigm attempts to improve technology and communication through the provision of probabilistic hazard information (PHI). The research and technology necessary to produce this information requires a substantial resource investment, but the societal value of the information may outweigh the costs. This study provides an initial estimate of this value by exploring public willingness to pay (WTP) for an app that provides continuously updated, geographically situated PHI that could be utilized during a tornado event. Findings indicate that the mean WTP, in a one-time payment, for this precise hazard information product is $7.53 per person. Aggregated to the US population, the estimated value is between $901 million and $1.56 billion. These findings indicate that federal agencies and private companies are likely to generate a substantial surplus by developing these products and will contribute to improving informed decision-making and protecting lives and property. AN - noaa:71979 DO - https://doi.org/10.1061/(ASCE)NH.1527-6996.0000444 IS - 2 J2 - Natural Hazards Review KW - Weather forecasting KW - Forecasting a Continuum of Environmental Threats (FACETs) KW - Probabilistic hazard information KW - Public willingness to pay KW - Weather forecasting PY - 2021 T2 - Natural Hazards Review T2 - Nat. Hazards Rev., 2021, 22(2): 04021004 TI - Public Willingness to Pay for Continuous and Probabilistic Hazard Information VL - 22 UR - https://repository.library.noaa.gov/view/noaa/71979 ER -
The Prediction of Potential Tornado Damage Intensity Using Machine Learning

Sessa, Michael F. ;

Trapp, Robert J.

2025 | Artif. Intell. Earth Syst., 4, e230113 | PDF

This study uses nine classification machine learning algorithms to examine their skill in making short-fused, storm-based predictions of significant or nonsignificant tornado damage intensity, conditioned upon tornadogenesis, using pretornadic mesocyclone characteristics and the near-storm environment. Radar predictors are from approximately 30 min ...

11/14/2025

Title : The Prediction of Potential Tornado Damage Intensity Using Machine Learning Personal Author(s) : Sessa, Michael F.;Trapp, Robert J.; Published Date : 2025 Source : Artif. Intell. Earth Syst., 4, e230113 DOI : https://doi.org/10.1175/AIES-D-23-0113.1 Journal Title : Artificial Intelligence for the Earth Systems Sessa, Michael F. and Trapp, Robert J. (2025). The Prediction of Potential Tornado Damage Intensity Using Machine Learning. 4(3). https://doi.org/10.1175/AIES-D-23-0113.1 Sessa, Michael F. and Trapp, Robert J. "The Prediction of Potential Tornado Damage Intensity Using Machine Learning" 4, no. 3 (2025), https://doi.org/10.1175/AIES-D-23-0113.1 Sessa, Michael F. and Trapp, Robert J. "The Prediction of Potential Tornado Damage Intensity Using Machine Learning" vol. 4, no. 3, 2025, https://doi.org/10.1175/AIES-D-23-0113.1 Export RIS Citation Information. TY - AU - Sessa, Michael F. AU - Trapp, Robert J. AB - This study uses nine classification machine learning algorithms to examine their skill in making short-fused, storm-based predictions of significant or nonsignificant tornado damage intensity, conditioned upon tornadogenesis, using pretornadic mesocyclone characteristics and the near-storm environment. Radar predictors are from approximately 30 min before tornadogenesis, while environmental predictors are from the model-analysis hour nearest but before the time of tornadogenesis. The most-skilled classifiers are logistic regression, random forests, and gradient boosting as measured by each model’s cross-validated accuracy (≈89%), precision (≈93%), and recall (≈73%) and other binary classification metrics. Learning curves indicate adequate training of models, and calibration curves reveal the reliability of predicted probabilities, with random forests being the most reliable. Also, permutation tests demonstrate the statistical significance of the cross-validated model accuracy. Out of the four radar predictors included in this study, radar-derived pretornadic mesocyclone width and differential velocity are the most important over convective mode and distance from the radar, followed by environmental vertical wind shear and composite parameters. Specifically, wider and stronger pretornadic mesocyclones in environments characterized by larger values of vertical wind shear and composite parameters increase the likelihood of significant tornadoes. The model results could build forecaster confidence in the anticipation of tornado damage intensity and aid forecasters in making informed impact-based warning tag decisions. This could better protect life and property by providing a summary of data relevant to potential tornado damage rating before tornado formation. Important future work includes the addition of other radar-based predictors and the development of a more diverse and realistic sample of tornadic events. AN - noaa:71978 DO - https://doi.org/10.1175/AIES-D-23-0113.1 IS - 3 J2 - Artificial Intelligence for the Earth Systems KW - Algorithms KW - Classification KW - Machine learning KW - Severe storms KW - Tornadoes KW - Mesocyclones KW - Storm environments KW - Severe storms KW - Tornadoes KW - Classification KW - Machine learning KW - Algorithms PY - 2025 T2 - Artificial Intelligence for the Earth Systems T2 - Artif. Intell. Earth Syst., 4, e230113 TI - The Prediction of Potential Tornado Damage Intensity Using Machine Learning VL - 4 UR - https://repository.library.noaa.gov/view/noaa/71978 ER -
Predicting Tropical Cyclone Track Forecast Errors Using a Probabilistic Neural Network

Martin A.

;

Barnes, Elizabeth A.

2025 | Artif. Intell. Earth Syst., 4, e240066 | PDF

A new method for estimating tropical cyclone track uncertainty is presented and tested. This method uses a neural network to predict a bivariate normal distribution, which serves as an estimate for track uncertainty. We train the network and make predictions on forecasts from the National Hurricane Center (NHC), which currently uses static error di ...

11/14/2025

Title : Predicting Tropical Cyclone Track Forecast Errors Using a Probabilistic Neural Network Personal Author(s) : Martin A.;Barnes, Elizabeth A.;Barnes, Randal J.;DeMaria, Mark;McGraw, Marie;Chirokova, Galina;Lu, Lixin; Published Date : 2025 Source : Artif. Intell. Earth Syst., 4, e240066 DOI : https://doi.org/10.1175/AIES-D-24-0066.1 Journal Title : Artificial Intelligence for the Earth Systems Martin A. et al. (2025). Predicting Tropical Cyclone Track Forecast Errors Using a Probabilistic Neural Network. 4(2). https://doi.org/10.1175/AIES-D-24-0066.1 Martin A. et al. "Predicting Tropical Cyclone Track Forecast Errors Using a Probabilistic Neural Network" 4, no. 2 (2025), https://doi.org/10.1175/AIES-D-24-0066.1 Martin A. et al. "Predicting Tropical Cyclone Track Forecast Errors Using a Probabilistic Neural Network" vol. 4, no. 2, 2025, https://doi.org/10.1175/AIES-D-24-0066.1 Export RIS Citation Information. TY - AU - Martin A. AU - Barnes, Elizabeth A. AU - Barnes, Randal J. AU - DeMaria, Mark AU - McGraw, Marie AU - Chirokova, Galina AU - Lu, Lixin AB - A new method for estimating tropical cyclone track uncertainty is presented and tested. This method uses a neural network to predict a bivariate normal distribution, which serves as an estimate for track uncertainty. We train the network and make predictions on forecasts from the National Hurricane Center (NHC), which currently uses static error distributions based on forecasts from the past 5 years for most applications. The neural network–based method produces uncertainty estimates that are dynamic and probabilistic. Further, the neural network–based method allows for probabilistic statements about tropical cyclone trajectories, including landfall probability, which we highlight. We show that our predictions are well calibrated using multiple metrics, that our method produces better uncertainty estimates than current NHC approaches, and that our method achieves similar performance to the Global Ensemble Forecast System. Once trained, the computational cost of predictions using this method is negligible, making it a strong candidate to improve the NHC’s operational estimations of tropical cyclone track uncertainty. AN - noaa:71977 DO - https://doi.org/10.1175/AIES-D-24-0066.1 IS - 2 J2 - Artificial Intelligence for the Earth Systems KW - Cyclones KW - Machine learning KW - Neural networks (Computer science) KW - Numerical weather forecasting KW - Probability forecasts (Meteorology) KW - Probability models KW - Probability distribution KW - Numerical weather prediction KW - Cyclones KW - Probability forecasts (Meteorology) KW - Numerical weather forecasting KW - Machine learning KW - Neural networks (Computer science) PY - 2025 T2 - Artificial Intelligence for the Earth Systems T2 - Artif. Intell. Earth Syst., 4, e240066 TI - Predicting Tropical Cyclone Track Forecast Errors Using a Probabilistic Neural Network VL - 4 UR - https://repository.library.noaa.gov/view/noaa/71977 ER -
Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts

Barnes Elizabeth A.

;

Barnes Randal J.

2023 | Environmental Data Science. 2023;2:e15 | PDF

A simple method for adding uncertainty to neural network regression tasks in earth science via estimation of a general probability distribution is described. Specifically, we highlight the sinh-arcsinh-normal distributions as particularly well suited for neural network uncertainty estimation. The methodology supports estimation of heteroscedastic, ...

11/14/2025

Title : Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts Personal Author(s) : Barnes Elizabeth A.;Barnes Randal J.;DeMaria, Mark; Published Date : 2023 Source : Environmental Data Science. 2023;2:e15 DOI : https://doi.org/10.1017/eds.2023.7 Journal Title : Environmental Data Science Barnes Elizabeth A. et al. (2023). Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts. 2https://doi.org/10.1017/eds.2023.7 Barnes Elizabeth A. and Barnes Randal J. and DeMaria, Mark "Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts" 2 (2023), https://doi.org/10.1017/eds.2023.7 Barnes Elizabeth A. et al. "Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts" vol. 2, 2023, https://doi.org/10.1017/eds.2023.7 Export RIS Citation Information. TY - AU - Barnes Elizabeth A. AU - Barnes Randal J. AU - DeMaria, Mark AB - A simple method for adding uncertainty to neural network regression tasks in earth science via estimation of a general probability distribution is described. Specifically, we highlight the sinh-arcsinh-normal distributions as particularly well suited for neural network uncertainty estimation. The methodology supports estimation of heteroscedastic, asymmetric uncertainties by a simple modification of the network output and loss function. Method performance is demonstrated by predicting tropical cyclone intensity forecast uncertainty and by comparing two other common methods for neural network uncertainty quantification (i.e., Bayesian neural networks and Monte Carlo dropout). The simple approach described here is intuitive and applicable when no prior exists and one just wishes to parameterize the output and its uncertainty according to some previously defined family of distributions. The authors believe it will become a powerful, go-to method moving forward. AN - noaa:71976 DO - https://doi.org/10.1017/eds.2023.7 J2 - Environmental Data Science KW - Cyclones KW - Machine learning KW - Neural networks (Computer science) KW - Sinh-arcsinh-normal distribution KW - Uncertainty quantification KW - Machine learning KW - Neural networks (Computer science) KW - Cyclones PY - 2023 T2 - Environmental Data Science T2 - Environmental Data Science. 2023;2:e15 TI - Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts VL - 2 UR - https://repository.library.noaa.gov/view/noaa/71976 ER -
Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles

Lee, ChangJae ;

Brewster, Keith A.

2025 | Wea. Forecasting, 39, 1545–1558 | PDF

Ensembles of convection-allowing model (CAM) forecasts are increasingly being used in operational numerical weather forecasting. Several approaches have been devised to find consensus among ensemble forecast fields, including the arithmetic ensemble mean and, more recently, the patchwise localized probability-matched (LPM) mean. However, difference ...

11/14/2025

Title : Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles Personal Author(s) : Lee, ChangJae;Brewster, Keith A.;Snook, Nathan;Spencer, Phillip;Park, Jun; Published Date : 2025 Source : Wea. Forecasting, 39, 1545–1558 DOI : https://doi.org/10.1175/WAF-D-23-0229.1 Journal Title : Weather and Forecasting Lee, ChangJae et al. (2025). Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles. 39(11). https://doi.org/10.1175/WAF-D-23-0229.1 Lee, ChangJae et al. "Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles" 39, no. 11 (2025), https://doi.org/10.1175/WAF-D-23-0229.1 Lee, ChangJae et al. "Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles" vol. 39, no. 11, 2025, https://doi.org/10.1175/WAF-D-23-0229.1 Export RIS Citation Information. TY - AU - Lee, ChangJae AU - Brewster, Keith A. AU - Snook, Nathan AU - Spencer, Phillip AU - Park, Jun AB - Ensembles of convection-allowing model (CAM) forecasts are increasingly being used in operational numerical weather forecasting. Several approaches have been devised to find consensus among ensemble forecast fields, including the arithmetic ensemble mean and, more recently, the patchwise localized probability-matched (LPM) mean. However, differences in spatial distribution and intensity of precipitation features among ensemble members make it difficult to construct an ensemble mean product that characterizes the consensus while preserving precipitation structures forecasted by the individual ensemble members. To overcome this problem, this study aims to develop and test a method for improving ensemble consensus precipitation forecasts by directly considering the spatial offsets among ensemble members. This study uses a multiscale spatial alignment technique to align the precipitation features of each ensemble member to a common location, and the spatial aligned mean (SAM) is obtained by averaging the realigned members. It is shown that implementing SAM and subsequently applying the LPM technique to the average of all aligned members (SAM–LPM) can significantly improve the warm season precipitation forecast scores using common metrics such as equitable threat score (ETS). Also, improvement in the structure of features of heavy rainfall is shown from summer 2023 flash-flooding cases. Thus, SAM and SAM–LPM can be excellent candidate methods for calculating an ensemble consensus and providing ensemble consensus guidance to forecasters. AN - noaa:71975 DO - https://doi.org/10.1175/WAF-D-23-0229.1 IS - 11 J2 - Weather and Forecasting KW - Numerical weather forecasting KW - Ensembles KW - Forecast verification KW - Mesoscale forecasting KW - Numerical weather prediction KW - Operational forecasting KW - Postprocessing KW - Numerical weather forecasting PY - 2025 T2 - Weather and Forecasting T2 - Wea. Forecasting, 39, 1545–1558 TI - Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles VL - 39 UR - https://repository.library.noaa.gov/view/noaa/71975 ER -
Combining Model and Observational Data Using Machine Learning for Short-Term Severe Weather Hazard Prediction

Loken, Eric D. ;

Clark, Adam J.

2025 | Artif. Intell. Earth Syst., 4, e240102 | PDF

The Warn-on-Forecast System (WoFS) is a convection-allowing ensemble that rapidly assimilates high-resolution radar, satellite, and other observational data to enhance forecasting capabilities at 0–6-h lead times. However, data latency and model spinup can reduce WoFS’ utility, especially within the first hour after initialization. On the other han ...

11/14/2025

Title : Combining Model and Observational Data Using Machine Learning for Short-Term Severe Weather Hazard Prediction Personal Author(s) : Loken, Eric D.;Clark, Adam J.;Calhoun, Kristin M.;Sandmael, Thea N.;Skinner, Patrick;Burke, Patrick C.;Heinselman, Pamela;Cintineo, John L.;Reinhart, Anthony; Published Date : 2025 Source : Artif. Intell. Earth Syst., 4, e240102 DOI : https://doi.org/10.1175/AIES-D-24-0102.1 Journal Title : Artificial Intelligence for the Earth Systems Loken, Eric D. et al. (2025). Combining Model and Observational Data Using Machine Learning for Short-Term Severe Weather Hazard Prediction. 4(4). https://doi.org/10.1175/AIES-D-24-0102.1 Loken, Eric D. et al. "Combining Model and Observational Data Using Machine Learning for Short-Term Severe Weather Hazard Prediction" 4, no. 4 (2025), https://doi.org/10.1175/AIES-D-24-0102.1 Loken, Eric D. et al. "Combining Model and Observational Data Using Machine Learning for Short-Term Severe Weather Hazard Prediction" vol. 4, no. 4, 2025, https://doi.org/10.1175/AIES-D-24-0102.1 Export RIS Citation Information. TY - AU - Loken, Eric D. AU - Clark, Adam J. AU - Calhoun, Kristin M. AU - Sandmael, Thea N. AU - Skinner, Patrick AU - Burke, Patrick C. AU - Heinselman, Pamela AU - Cintineo, John L. AU - Reinhart, Anthony AB - The Warn-on-Forecast System (WoFS) is a convection-allowing ensemble that rapidly assimilates high-resolution radar, satellite, and other observational data to enhance forecasting capabilities at 0–6-h lead times. However, data latency and model spinup can reduce WoFS’ utility, especially within the first hour after initialization. On the other hand, Probability of Severe (ProbSevere), version 2 (PS2), is a set of statistical models that considers radar, satellite, and numerical weather prediction environment data to provide skillful severe hail, wind, and tornado probabilities at 0–1-h lead times, updated every 2 min. To enable seamless, probabilistic severe weather hazard forecasts leveraging the strengths of both systems, a random forest (RF) algorithm is developed that considers predictors from both WoFS and PS2. Experiments are conducted using different combinations of predictors at various spatial radii and lead times, and predictor importance is assessed. RFs configured using predictors from both WoFS and PS2 are found to outperform RFs configured from only one system, with the greatest gains in forecast skill from the all-predictor RFs coming at lead times less than 90 min. PS2 (WoFS) predictors are identified as more important at earlier (later) lead times. Severe hail forecasts were the most skillful of the three hazards, followed by severe wind and tornadoes. This new algorithm shows how combining complementary datasets using machine learning can improve short-term severe hazard guidance. Upcoming work will report on the results from testing during real-time forecasting experiments. AN - noaa:71974 DO - https://doi.org/10.1175/AIES-D-24-0102.1 IS - 4 J2 - Artificial Intelligence for the Earth Systems KW - Artificial intelligence KW - Decision trees KW - Machine learning KW - Short-range prediction KW - Model interpretation and visualization KW - Nowcasting KW - Artificial intelligence KW - Machine learning KW - Decision trees PY - 2025 T2 - Artificial Intelligence for the Earth Systems T2 - Artif. Intell. Earth Syst., 4, e240102 TI - Combining Model and Observational Data Using Machine Learning for Short-Term Severe Weather Hazard Prediction VL - 4 UR - https://repository.library.noaa.gov/view/noaa/71974 ER -
The impact of vertical model levels on the prediction of MJO teleconnections. Part II: The stratospheric pathway in the UFS global coupled model

Garfinkel, Chaim I.

;

Wu, Zheng

2025 | Climate Dynamics (2025) 63:36 | PDF

This study continues the evaluation of the prediction of MJO teleconnections in two versions of the NOAA Unified Forecast System (UFS): prototype 5 (UFS5) and prototype 6 (UFS6). The key difference between the two prototypes is in the number of vertical layers (127 in UFS6 vs. 64 in UFS5) and model top (80 km in UFS6 vs. 54 km in UFS5), and the rol ...

11/14/2025

Title : The impact of vertical model levels on the prediction of MJO teleconnections. Part II: The stratospheric pathway in the UFS global coupled model Personal Author(s) : Garfinkel, Chaim I.;Wu, Zheng;Yadav, Priyanka;Lawrence, Zachary;Domeisen, Daniela I.V.;Zheng, Cheng;Wang, Jiabao;Jenney, Andrea M.;Kim, Hyemi;Schwartz, Chen;Stan, Cristiana; Published Date : 2025 Source : Climate Dynamics (2025) 63:36 DOI : https://doi.org/10.1007/s00382-024-07512-8 Journal Title : Climate Dynamics Garfinkel, Chaim I. et al. (2025). The impact of vertical model levels on the prediction of MJO teleconnections. Part II: The stratospheric pathway in the UFS global coupled model. 63https://doi.org/10.1007/s00382-024-07512-8 Garfinkel, Chaim I. et al. "The impact of vertical model levels on the prediction of MJO teleconnections. Part II: The stratospheric pathway in the UFS global coupled model" 63 (2025), https://doi.org/10.1007/s00382-024-07512-8 Garfinkel, Chaim I. et al. "The impact of vertical model levels on the prediction of MJO teleconnections. Part II: The stratospheric pathway in the UFS global coupled model" vol. 63, 2025, https://doi.org/10.1007/s00382-024-07512-8 Export RIS Citation Information. TY - AU - Garfinkel, Chaim I. AU - Wu, Zheng AU - Yadav, Priyanka AU - Lawrence, Zachary AU - Domeisen, Daniela I.V. AU - Zheng, Cheng AU - Wang, Jiabao AU - Jenney, Andrea M. AU - Kim, Hyemi AU - Schwartz, Chen AU - Stan, Cristiana AB - This study continues the evaluation of the prediction of MJO teleconnections in two versions of the NOAA Unified Forecast System (UFS): prototype 5 (UFS5) and prototype 6 (UFS6). The key difference between the two prototypes is in the number of vertical layers (127 in UFS6 vs. 64 in UFS5) and model top (80 km in UFS6 vs. 54 km in UFS5), and the role of this increased resolution for the stratospheric pathway of MJO teleconnections is explored. The higher resolution prototype (UFS6) displays larger biases in its representation of tropospheric stationary waves, though both simulate a reasonable flux of wave activity entering the stratosphere. The stratospheric polar vortex in both prototypes is overly-sensitive to incoming wave activity, while both simulate a reasonable downward propagation of vortex anomalies within the stratosphere and down to the troposphere. The net effect is that both simulate the stratospheric pathway of the MJO better than has been documented for any forecasting system, though the hindcast period available for UFS differs from that used in previous studies. This allows them to predict, e.g., near-surface temperature over Eurasia with some skill on subseasonal timescales (week 3 to 5). However, this success could be the result of “two wrongs making a right”, and as individual biases are fixed, skill could temporarily be reduced. Overall, the two prototypes show similar performance in simulating the stratospheric route, suggesting that in the UFS, the increase in model vertical resolution has a limited impact on the prediction of MJO teleconnections via the stratosphere. AN - noaa:71973 DO - https://doi.org/10.1007/s00382-024-07512-8 J2 - Climate Dynamics KW - Madden-Julian oscillation KW - Subseasonal predictability KW - Stratosphere-troposphere coupling KW - Madden-Julian oscillation PY - 2025 T2 - Climate Dynamics T2 - Climate Dynamics (2025) 63:36 TI - The impact of vertical model levels on the prediction of MJO teleconnections. Part II: The stratospheric pathway in the UFS global coupled model VL - 63 UR - https://repository.library.noaa.gov/view/noaa/71973 ER -
How Likely is That Chance of Thunderstorms? A Study of How National Weather Service Forecast Offices Use Words of Estimative Probability and What They Mean to the Public

Lenhardt, Emily D. ;

Cross, Rachael N.

2020 | J. Operational Meteor., 8 (5), 64-78 | PDF

One of the challenges when communicating forecast information to the public is properly contextualizing uncertainty. No forecast is ever certain, as no meteorological phenomenon is guaranteed to occur. As such, the uncertainty in forecast information should be communicated in a way that makes sense to end users. Previous studies of the communicatio ...

11/14/2025

Title : How Likely is That Chance of Thunderstorms? A Study of How National Weather Service Forecast Offices Use Words of Estimative Probability and What They Mean to the Public Personal Author(s) : Lenhardt, Emily D.;Cross, Rachael N.;Krocak, Makenzie J.;Ripberger, Joseph T.;Ernst, Sean R.;Silva, Carol L.;Jenkins-Smith, Hank C.; Published Date : 2020 Source : J. Operational Meteor., 8 (5), 64-78 DOI : https://doi.org/10.15191/nwajom.2020.0805 Journal Title : Journal of Operational Meteorology Lenhardt, Emily D. et al. (2020). How Likely is That Chance of Thunderstorms? A Study of How National Weather Service Forecast Offices Use Words of Estimative Probability and What They Mean to the Public. 8(5). https://doi.org/10.15191/nwajom.2020.0805 Lenhardt, Emily D. et al. "How Likely is That Chance of Thunderstorms? A Study of How National Weather Service Forecast Offices Use Words of Estimative Probability and What They Mean to the Public" 8, no. 5 (2020), https://doi.org/10.15191/nwajom.2020.0805 Lenhardt, Emily D. et al. "How Likely is That Chance of Thunderstorms? A Study of How National Weather Service Forecast Offices Use Words of Estimative Probability and What They Mean to the Public" vol. 8, no. 5, 2020, https://doi.org/10.15191/nwajom.2020.0805 Export RIS Citation Information. TY - AU - Lenhardt, Emily D. AU - Cross, Rachael N. AU - Krocak, Makenzie J. AU - Ripberger, Joseph T. AU - Ernst, Sean R. AU - Silva, Carol L. AU - Jenkins-Smith, Hank C. AB - One of the challenges when communicating forecast information to the public is properly contextualizing uncertainty. No forecast is ever certain, as no meteorological phenomenon is guaranteed to occur. As such, the uncertainty in forecast information should be communicated in a way that makes sense to end users. Previous studies of the communication of probabilistic information suggest that, although the general public are more apt to communicate uncertainty with words of estimative probability (WEPs), they prefer to receive uncertainty information numerically. Other work has suggested that a combination of numbers and WEPs is the best method for communicating probability, but fewer research studies have assessed the communication and interpretation of probabilistic meteorological information. In this study, we code 8900 tweets from the National Weather Service Weather Forecast Offices (WFOs) and analyze them to find how forecasters communicate probabilistic forecast information to the public via Twitter. This analysis reveals that WFO messaging is dominated by WEPs, with few numerical descriptions of probability. These WEPs are generally vague, unqualified notions of probability that may impede the public’s ability to interpret the information that forecasters are trying to communicate. Based on this analysis, two publicly fielded surveys also are analyzed in order to understand how participants tend to interpret the most common qualified and unqualified WEPs that WFOs used on Twitter. Though participants generally interpret qualified WEPs more consistently than unqualified WEPs, both categories featured a wide range of interpretations that suggest both types of WEPs are vaguely defined for the general public. AN - noaa:71972 DO - https://doi.org/10.15191/nwajom.2020.0805 IS - 5 J2 - Journal of Operational Meteorology KW - Thunderstorms KW - Weather forecasting KW - Words of estimative probability KW - National Weather Service (NWS) KW - Weather Forecast Office (WFO) KW - Tweets KW - Thunderstorms KW - Weather forecasting PY - 2020 T2 - Journal of Operational Meteorology T2 - J. Operational Meteor., 8 (5), 64-78 TI - How Likely is That Chance of Thunderstorms? A Study of How National Weather Service Forecast Offices Use Words of Estimative Probability and What They Mean to the Public VL - 8 UR - https://repository.library.noaa.gov/view/noaa/71972 ER -
The potential impacts of improved MJO prediction on the prediction of MJO teleconnections in the UFS global fully coupled model

Wang, Jiabao

;

Domeisen, Daniela I.V.

2025 | Climate Dynamics (2025) 63:312 | PDF

The value of Madden-Julian oscillation (MJO) prediction for extratropical subseasonal forecasts hinges on the assumption that reliable MJO simulation translates to reliable simulation of its teleconnections. This study examines the prediction of the MJO and its teleconnections in two recently developed NOAA Unified Forecast System (UFS) coupled mod ...

11/14/2025

Supporting Files

Title : The potential impacts of improved MJO prediction on the prediction of MJO teleconnections in the UFS global fully coupled model Personal Author(s) : Wang, Jiabao;Domeisen, Daniela I.V.;Garfinkel, Chaim I.;Jenney, Andrea M.;Kim, Hyemi;Wu, Zheng;Zheng, Cheng;Stan, Cristiana; Published Date : 2025 Source : Climate Dynamics (2025) 63:312 DOI : https://doi.org/10.1007/s00382-025-07783-9 Journal Title : Climate Dynamics Wang, Jiabao et al. (2025). The potential impacts of improved MJO prediction on the prediction of MJO teleconnections in the UFS global fully coupled model. 63https://doi.org/10.1007/s00382-025-07783-9 Wang, Jiabao et al. "The potential impacts of improved MJO prediction on the prediction of MJO teleconnections in the UFS global fully coupled model" 63 (2025), https://doi.org/10.1007/s00382-025-07783-9 Wang, Jiabao et al. "The potential impacts of improved MJO prediction on the prediction of MJO teleconnections in the UFS global fully coupled model" vol. 63, 2025, https://doi.org/10.1007/s00382-025-07783-9 Export RIS Citation Information. TY - AU - Wang, Jiabao AU - Domeisen, Daniela I.V. AU - Garfinkel, Chaim I. AU - Jenney, Andrea M. AU - Kim, Hyemi AU - Wu, Zheng AU - Zheng, Cheng AU - Stan, Cristiana AB - The value of Madden-Julian oscillation (MJO) prediction for extratropical subseasonal forecasts hinges on the assumption that reliable MJO simulation translates to reliable simulation of its teleconnections. This study examines the prediction of the MJO and its teleconnections in two recently developed NOAA Unified Forecast System (UFS) coupled model prototypes: Prototype 7 (UFS7) and Prototype 8 (UFS8). The MJO is skillfully predicted at a lead time of 27 days in UFS8, which is a considerable improvement (~ one-week skill increase) compared to UFS7. The potential effect of this improvement on MJO teleconnections via both tropospheric and stratospheric pathways is examined. UFS8 captures the pattern and amplitude of the geopotential height response in the North Pacific reasonably well and its evolution following active MJO events. The dipole response in the storm tracks over the North Pacific after active MJO events is also better captured in UFS8. In addition, the upward wave propagation and subsequent weakening of the polar vortex are better simulated in UFS8, with comparable strength to that in the reanalysis. Despite the notable improvements listed above, some biases remain: too-fast MJO propagation, an underestimation of geopotential height variability in the North Atlantic and Europe, an underestimation of the precipitation response, failure to capture the temperature evolution, and weaker MJO impacts on the NAO. This study suggests the potential of increasing the MJO teleconnection prediction skill, although not in all variables, by improving MJO predictions in dynamical models with more coupled components and upgraded model physics. AN - noaa:71971 DO - https://doi.org/10.1007/s00382-025-07783-9 J2 - Climate Dynamics KW - Madden-Julian oscillation KW - MJO teleconnections KW - Subseasonal-to-seasonal forecast KW - Unified Forecast System (UFS) KW - UFS fully coupled model KW - Tropospheric and stratospheric pathways KW - Madden-Julian oscillation PY - 2025 T2 - Climate Dynamics T2 - Climate Dynamics (2025) 63:312 TI - The potential impacts of improved MJO prediction on the prediction of MJO teleconnections in the UFS global fully coupled model VL - 63 UR - https://repository.library.noaa.gov/view/noaa/71971 ER -
Impacts of Initial Condition Perturbation Blending in 10- and 40-Member Convection-Allowing Ensemble Forecasts

Johnson, Aaron ;

Wang, Xuguang

2024 | Mon. Wea. Rev., 152, 1421–1441 | PDF

A series of convection-allowing 36-h ensemble forecasts during the 2018 spring season are used to better understand the impacts of ensemble configuration and blending different sources of initial condition (IC) perturbation. Ten- and forty-member ensemble configurations are initialized with the multiscale IC perturbations generated as a product of ...

11/14/2025

Title : Impacts of Initial Condition Perturbation Blending in 10- and 40-Member Convection-Allowing Ensemble Forecasts Personal Author(s) : Johnson, Aaron;Wang, Xuguang; Published Date : 2024 Source : Mon. Wea. Rev., 152, 1421–1441 DOI : https://doi.org/10.1175/MWR-D-23-0188.1 Journal Title : Monthly Weather Review Johnson, Aaron and Wang, Xuguang (2024). Impacts of Initial Condition Perturbation Blending in 10- and 40-Member Convection-Allowing Ensemble Forecasts. 152(6). https://doi.org/10.1175/MWR-D-23-0188.1 Johnson, Aaron and Wang, Xuguang "Impacts of Initial Condition Perturbation Blending in 10- and 40-Member Convection-Allowing Ensemble Forecasts" 152, no. 6 (2024), https://doi.org/10.1175/MWR-D-23-0188.1 Johnson, Aaron and Wang, Xuguang "Impacts of Initial Condition Perturbation Blending in 10- and 40-Member Convection-Allowing Ensemble Forecasts" vol. 152, no. 6, 2024, https://doi.org/10.1175/MWR-D-23-0188.1 Export RIS Citation Information. TY - AU - Johnson, Aaron AU - Wang, Xuguang AB - A series of convection-allowing 36-h ensemble forecasts during the 2018 spring season are used to better understand the impacts of ensemble configuration and blending different sources of initial condition (IC) perturbation. Ten- and forty-member ensemble configurations are initialized with the multiscale IC perturbations generated as a product of convective-scale data assimilation (MULTI) and initialized with the MULTI IC perturbations blended with IC perturbations downscaled from coarser-resolution ensembles (BLEND). The forecast performance of both precipitation and nonprecipitation variables is consistently improved by the larger ensemble size. The benefit of the larger ensemble is largely, but not entirely, due to compensating for underdispersion in the fixed-physics ensemble configuration. A consistent improvement in precipitation forecast skill results from blending in the 10-member ensemble configuration, corresponding to a reduction in the ensemble calibration error (i.e., reliability component of Brier score). In the 40-member ensemble configuration, the advantage of blending is limited to the ∼18–22-h lead times at all precipitation thresholds and the ∼35–36-h lead times at the lowest threshold, both corresponding to an improved resolution component of the Brier score. The advantage of blending in the 40-member ensemble during the diurnal convection maximum of ∼18–22-h lead times is primarily due to cases with relatively weak synoptic-scale forcing, while advantages at later lead times beyond ∼30-h lead time are most prominent on cases with relatively strong synoptic-scale forcing. The impacts of blending and ensemble configuration on forecasts of nonprecipitation variables are generally consistent with the impacts on the precipitation forecasts. AN - noaa:71970 DO - https://doi.org/10.1175/MWR-D-23-0188.1 IS - 6 J2 - Monthly Weather Review KW - Numerical weather forecasting KW - Probability forecasts (Meteorology) KW - Ensembles KW - Numerical weather prediction KW - Probability models KW - Probability distribution KW - Numerical weather forecasting KW - Probability forecasts (Meteorology) PY - 2024 T2 - Monthly Weather Review T2 - Mon. Wea. Rev., 152, 1421–1441 TI - Impacts of Initial Condition Perturbation Blending in 10- and 40-Member Convection-Allowing Ensemble Forecasts VL - 152 UR - https://repository.library.noaa.gov/view/noaa/71970 ER -
Fishing information, May 1977, no. 5

Renner, James A. (editor)

1977 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, May 1977, no. 5 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1977 URL : https://repository.library.noaa.gov/view/noaa/71965 Renner, James A. (editor) (1977). Fishing information, May 1977, no. 5. Renner, James A. (editor) "Fishing information, May 1977, no. 5" (1977) Renner, James A. (editor) "Fishing information, May 1977, no. 5" , 1977 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71965 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1977 TI - Fishing information, May 1977, no. 5 UR - https://repository.library.noaa.gov/view/noaa/71965 ER -
Fishing information, April 1977, no. 4

Renner, James A. (editor)

1977 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, April 1977, no. 4 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1977 URL : https://repository.library.noaa.gov/view/noaa/71964 Renner, James A. (editor) (1977). Fishing information, April 1977, no. 4. Renner, James A. (editor) "Fishing information, April 1977, no. 4" (1977) Renner, James A. (editor) "Fishing information, April 1977, no. 4" , 1977 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71964 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1977 TI - Fishing information, April 1977, no. 4 UR - https://repository.library.noaa.gov/view/noaa/71964 ER -
Fishing information, March 1977, no. 3

Renner, James A. (editor)

1977 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, March 1977, no. 3 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1977 URL : https://repository.library.noaa.gov/view/noaa/71963 Renner, James A. (editor) (1977). Fishing information, March 1977, no. 3. Renner, James A. (editor) "Fishing information, March 1977, no. 3" (1977) Renner, James A. (editor) "Fishing information, March 1977, no. 3" , 1977 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71963 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1977 TI - Fishing information, March 1977, no. 3 UR - https://repository.library.noaa.gov/view/noaa/71963 ER -
Fishing information, February 1977, no. 2

Renner, James A. (editor)

1977 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, February 1977, no. 2 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1977 URL : https://repository.library.noaa.gov/view/noaa/71962 Renner, James A. (editor) (1977). Fishing information, February 1977, no. 2. Renner, James A. (editor) "Fishing information, February 1977, no. 2" (1977) Renner, James A. (editor) "Fishing information, February 1977, no. 2" , 1977 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71962 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1977 TI - Fishing information, February 1977, no. 2 UR - https://repository.library.noaa.gov/view/noaa/71962 ER -
Fishing information, January 1977, no. 1

Renner, James A. (editor)

1977 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, January 1977, no. 1 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1977 URL : https://repository.library.noaa.gov/view/noaa/71961 Renner, James A. (editor) (1977). Fishing information, January 1977, no. 1. Renner, James A. (editor) "Fishing information, January 1977, no. 1" (1977) Renner, James A. (editor) "Fishing information, January 1977, no. 1" , 1977 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71961 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1977 TI - Fishing information, January 1977, no. 1 UR - https://repository.library.noaa.gov/view/noaa/71961 ER -
Fishing information, December 1979, no. 12

Renner, James A. (editor)

1980 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, December 1979, no. 12 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1980 URL : https://repository.library.noaa.gov/view/noaa/71960 Renner, James A. (editor) (1980). Fishing information, December 1979, no. 12. Renner, James A. (editor) "Fishing information, December 1979, no. 12" (1980) Renner, James A. (editor) "Fishing information, December 1979, no. 12" , 1980 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71960 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1980 TI - Fishing information, December 1979, no. 12 UR - https://repository.library.noaa.gov/view/noaa/71960 ER -
Fishing information, December 1980, no. 12

Renner, James A. (editor)

1981 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, December 1980, no. 12 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1981 URL : https://repository.library.noaa.gov/view/noaa/71959 Renner, James A. (editor) (1981). Fishing information, December 1980, no. 12. Renner, James A. (editor) "Fishing information, December 1980, no. 12" (1981) Renner, James A. (editor) "Fishing information, December 1980, no. 12" , 1981 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71959 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1981 TI - Fishing information, December 1980, no. 12 UR - https://repository.library.noaa.gov/view/noaa/71959 ER -
Fishing information, November 1980, no. 11

Renner, James A. (editor)

1981 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, November 1980, no. 11 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1981 URL : https://repository.library.noaa.gov/view/noaa/71958 Renner, James A. (editor) (1981). Fishing information, November 1980, no. 11. Renner, James A. (editor) "Fishing information, November 1980, no. 11" (1981) Renner, James A. (editor) "Fishing information, November 1980, no. 11" , 1981 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71958 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1981 TI - Fishing information, November 1980, no. 11 UR - https://repository.library.noaa.gov/view/noaa/71958 ER -
Fishing information, October 1980, no. 10

Renner, James A. (editor)

1980 | pdf

This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurf ...

11/14/2025

Title : Fishing information, October 1980, no. 10 Personal Author(s) : Renner, James A. (editor) Corporate Authors(s) : Southwest Fisheries Center (U.S.) Published Date : 1980 URL : https://repository.library.noaa.gov/view/noaa/71957 Renner, James A. (editor) (1980). Fishing information, October 1980, no. 10. Renner, James A. (editor) "Fishing information, October 1980, no. 10" (1980) Renner, James A. (editor) "Fishing information, October 1980, no. 10" , 1980 Export RIS Citation Information. TY - AU - Renner, James A. (editor) A2 - Southwest Fisheries Center (U.S.) AB - This publication, Fishing Information, appears monthly and contains 1) fishery advisory information, 2) a narrative description of pertinent surface temperature conditions, 3) charts of winds and pressures for the eastern North Pacific, 4) charts of sea surface temperature for the North Pacific and eastern tropical Pacific, and 5) charts of subsurface temperature structure in the eastern North Pacific. AB - Earlier title : California fishery market news monthly summary, Part II, Fishing information AB - Later title : Oceanographic monthly summary AB - Later title : United States. National Weather Service. Gulfstream AB - Has supplement : Fishing information. Supplement AN - noaa:71957 KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Observations KW - Ocean temperature KW - Fisheries KW - Fishery management KW - Marine meteorology KW - Ocean temperature KW - Observations PY - 1980 TI - Fishing information, October 1980, no. 10 UR - https://repository.library.noaa.gov/view/noaa/71957 ER -

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