Abstract One of the most costly effects of climate change will be its impact on extreme weather events, including tropical cyclones (TCs). Understanding these changes is of growing importance, and high resolution global climate models are providing potential for such studies, specifically for TCs. Beyond the difficulties associated with TC behavior in a warming climate, the extratropical transition (ET) of TCs into post-tropical cyclones (PTCs) creates another challenge when understanding these events and any potential future changes. PTCs can produce excessive rainfall despite losing their original tropical characteristics. The present study examines the representation of PTCs and their precipitation in three high resolution (25–50 km) climate models: CNRM, MRI, and HadGEM. All three of these models agree on a simulated decrease in TC and PTC events in the future warming scenario, yet they lack consistency in simulated regional patterns of these changes, which is further evident in regional changes in PTC-related precipitation. The models also struggle with their represented intensity evolution of storms during and after the ET process. Despite these limitations in simulating intensity and regional characteristics, the models all simulate a shift toward more frequent rain rates above 10 mm h−1in PTCs. These high rain rates become 4%–12% more likely in the warmer climate scenario, resulting in a 5%–12% increase in accumulated rainfall from these rates. 
                        more » 
                        « less   
                    This content will become publicly available on November 1, 2025
                            
                            Verification of Operational Forecast Models in Cases of Extratropical Transition of North Atlantic Hurricanes
                        
                    
    
            Abstract Operational forecast models are necessary for the prediction of weather events in real time. Verification of these models must be performed to assess model skills and areas in need of improvement, particularly with different types of weather events that may occur. Despite the devastating impacts that can be caused by tropical cyclones (TCs) that undergo extratropical transition (ET) and become post-tropical cyclones (PTCs), these storms have not been extensively studied in the context of short-term weather prediction. This study completes the first analysis of the Global Forecast System (GFS) and a preoperational version of the newly operational Hurricane Analysis and Forecast System (HAFS) models in forecasting the occurrence of ET and the rainfall associated with ET storms in the North Atlantic basin. GFS’s skill exceeds that of HAFS in forecasting the occurrence of ET, but HAFS tends to have lower track and rain-rate errors in the fully tropical phase of ET storms’ life cycles. Both models simulate rain rates that are often too high near the storm center and fail to capture the larger area of moderate rain rates that greatly contributes to total rainfall accumulation. The discrepancies in rain rates between the models and Integrated Multi-satellitE Retrievals for GPM (IMERG) could be attributed to the models’ tendency to keep storms too intense and too compact with an overly strong warm core, even throughout the ET process. 
        more » 
        « less   
        
    
                            - Award ID(s):
- 2244917
- PAR ID:
- 10573120
- Publisher / Repository:
- AMS
- Date Published:
- Journal Name:
- Weather and Forecasting
- Volume:
- 39
- Issue:
- 11
- ISSN:
- 0882-8156
- Page Range / eLocation ID:
- 1695 to 1714
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            Abstract Tropical cyclone (TC) precipitation poses serious hazards including freshwater flooding. High-resolution hurricane models predict the location and intensity of TC rainfall, which can influence local evacuation and preparedness policies. This study evaluates 0–72-h precipitation forecasts from two experimental models, the Hurricane Analysis and Forecast System (HAFS) model and the basin-scale Hurricane Weather Research and Forecasting (HWRF-B) Model, for 2020 North Atlantic landfalling TCs. We use an object-based method that quantifies the shape and size of the forecast and observed precipitation. Precipitation objects are then compared for light, moderate, and heavy precipitation using spatial metrics (e.g., area, perimeter, elongation). Results show that both models forecast precipitation that is too connected, too close to the TC center, and too enclosed around the TC center. Collectively, these spatial biases suggest that the model forecasts are too intense even though there is a negative intensity bias for both models, indicating there may be an inconsistency between the precipitation configuration and the maximum sustained winds in the model forecasts. The HAFS model struggles with forecasting stratiform versus convective precipitation and with the representation of lighter (stratiform) precipitation during the first 6 h after initialization. No such spinup issues are seen in the HWRF-B forecasts, which instead exhibit systematic biases at all lead times and systematic issues across all rain-rate thresholds. Future work will investigate spinup issues in the HAFS model forecast and how the microphysics parameterization affects the representation of precipitation in both models.more » « less
- 
            null (Ed.)Abstract The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conventional “grid-by-grid analysis,” the object-based approach provides a promising way to diagnose spatial properties of storms, trace them through space and time, and connect their accuracy to storm types and input data sources. The evolution of two tropical cyclones are generally captured by IMERG and NU-WRF, while the less organized spatial patterns of two mesoscale convective systems pose challenges for both. NU-WRF rain rates are generally more accurate, while IMERG better captures storm location and shape. Both show higher skill in detecting large, intense storms compared to smaller, weaker storms. IMERG’s accuracy depends on the input microwave and infrared data sources; NU-WRF does not appear to exhibit this dependence. Findings highlight that an object-oriented view can provide deeper insights into satellite precipitation performance and that the satellite precipitation community should further explore the potential for “hybrid” data-driven and physics-driven estimates in order to make optimal usage of satellite observations.more » « less
- 
            Abstract Sierras de Córdoba (Argentina) is characterized by the occurrence of extreme precipitation events during the austral warm season. Heavy precipitation in the region has a large societal impact, causing flash floods. This motivates the forecast performance evaluation of 24-h accumulated precipitation and vertical profiles of atmospheric variables from different numerical weather prediction (NWP) models with the final aim of helping water management in the region. The NWP models evaluated include the Global Forecast System (GFS), which parameterizes convection, and convection-permitting simulations of the Weather Research and Forecasting (WRF) Model configured by three institutions: University of Illinois at Urbana–Champaign (UIUC), Colorado State University (CSU), and National Meteorological Service of Argentina (SMN). These models were verified with daily accumulated precipitation data from rain gauges and soundings during the RELAMPAGO-CACTI field campaign. Generally all configurations of the higher-resolution WRFs outperformed the lower-resolution GFS based on multiple metrics. Among the convection-permitting WRF Models, results varied with respect to rainfall threshold and forecast lead time, but the WRFUIUC mostly performed the best. However, elevation-dependent biases existed among the models that may impact the use of the data for different applications. There is a dry (moist) bias in lower (upper) pressure levels which is most pronounced in the GFS. For Córdoba an overestimation of the northern flow forecasted by the NWP configurations at lower levels was encountered. These results show the importance of convection-permitting forecasts in this region, which should be complementary to the coarser-resolution global model forecasts to help various users and decision-makers.more » « less
- 
            Abstract Rain in tropical cyclones is studied using eight time series of underwater ambient sound at 40–50 kHz with wind speeds up to 45 m s−1beneath three tropical cyclones. At tropical cyclone wind speeds, rain- and wind-generated sound levels are comparable, and therefore rain cannot be detected by sound level alone. A rain detection algorithm that is based on the variations of 5–30-kHz sound levels with periods longer than 20 s and shorter than 30 min is proposed. Faster fluctuations (<20 s) are primarily due to wave breaking, and slower ones (>30 min) are due to overall wind variations. Higher-frequency sound (>30 kHz) is strongly attenuated by bubble clouds. This approach is supported by observations that, for wind speeds < 40 m s−1, the variation in sound level is much larger than that expected from observed wind variations and is roughly comparable to that expected from rain variations. The hydrophone results are consistent with rain estimates by the Tropical Rainfall Measuring Mission (TRMM) satellite and with Stepped-Frequency Microwave Radiometer (SFMR) and radar estimates by surveillance flights. The observations indicate that the rain-generated sound fluctuations have broadband acoustic spectra centered around 10 kHz. Acoustically detected rain events usually last for a few minutes. The data used in this study are insufficient to produce useful estimation of rain rate from ambient sound because of limited quantity and accuracy of the validation data. The frequency dependence of sound variations suggests that quantitative rainfall algorithms from ambient sound may be developed using multiple sound frequencies. Significance StatementRain is an indispensable process in forecasting the intensity and path of tropical cyclones. However, its role in the air–sea interaction is still poorly understood, and its parameterization in numerical models is still in development. In this work, we analyzed sound measurements made by hydrophones on board Lagrangian floats beneath tropical cyclones. We find that wind, rain, and breaking waves each have distinctive signatures in underwater ambient sound. We suggest that the air–sea dynamic processes in tropical cyclones can be explored by listening to ambient sound using hydrophones beneath the sea surface.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
