TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets

Research on the Atmospheric River (AR) in regions beyond the midlatitudes has gained increasing attention in recent years. However, detection algorithms basically rely on image recognition, which often results in errors when scrutinizing the moisture filament embedded with tropical cyclones (TCs). Therefore, the ARs over the Asia–Pacific monsoon region, where the coexistence of AR and TC frequently occurs, from 1981–2020 are investigated. To reduce erroneous identification and specifically separate the AR and TC, an additional objective approach to filter out the TC circulation according to the objectively estimated radius of the outermost closed isobar (ROCI) is incorporated into the existing detection algorithm. In addition, two modern reanalysis datasets, MERRA-2 and ERA5, are utilized to evaluate the sensitivity of the modified algorithm to the geometric criteria and intensity thresholds of the moisture features and different reanalysis inputs. Based on the level of spatial overlap between the detected ARs and contiguous rainfall areas (CRAs) and the sensitivity of AR frequency to different thresholds and algorithms, the detection scheme performs better when the integrated vapor transport anomaly (IVTA) used for identification is computed from ERA5 and its intensity threshold is lowered to 200 kg⋅m −1 ⋅s −1 . The CRAs are classified into those associated with AR, TC, both of them, or neither of them, depending on the algorithm outputs. An analysis of the rainfall intensity of the CRAs revealed that, compared with TC (80–100 mm⋅day −1 ), AR generally requires terrains to generate more rainfall of up to 80 mm⋅day −1 . Otherwise, the average rainfall intensity of AR is approximately 50–60 mm⋅day −1 . The average strongest rainfall tends to occur within the TC accompanied by the AR (100–120 mm⋅day −1 ). Regional averages indicate that AR acts as the primary source of annual rainfall in Northeast Asia. In contrast, TC tends to contribute more than AR in the western North Pacific and South China Sea.

The wettest period during the CalWater-2014 winter field campaign occurred with a long-lived, intense atmospheric river (AR) that impacted California on 7–10 February. The AR was maintained in conjunction with the development and propagation of three successive mesoscale frontal waves. Based on Lagrangian trajectory analysis, moist air of tropical origin was tapped by the AR and was subsequently transported into California. Widespread heavy precipitation (200–400 mm) fell across the coastal mountain ranges northwest of San Francisco and across the northern Sierra Nevada, although only modest flooding ensued due to anomalously dry antecedent conditions. A NOAA G-IV aircraft flew through two of the frontal waves in the AR environment offshore during a ~24-h period. Parallel dropsonde curtains documented key three-dimensional thermodynamic and kinematic characteristics across the AR and the frontal waves prior to landfall. The AR characteristics varied, depending on the location of the cross section through the frontal waves. A newly implemented tail-mounted Doppler radar on the G-IV simultaneously captured coherent precipitation features. Along the coast, a 449-MHz wind profiler and collocated global positioning system (GPS) receiver documented prolonged AR conditions linked to the propagation of the three frontal waves and highlighted the orographic character of the coastal-mountain rainfall with the waves’ landfall. A vertically pointing S-PROF radar in the coastal mountains provided detailed information on the bulk microphysical characteristics of the rainfall. Farther inland, a pair of 915-MHz wind profilers and GPS receivers quantified the orographic precipitation forcing as the AR ascended the Sierra Nevada, and as the terrain-induced Sierra barrier jet ascended the northern terminus of California’s Central Valley.

Nadal-Caraballo, N.C.; Campbell, M.O.; Gonzalez, V.M.; Torres, M.J.; Melby, J.A., and Taflanidis, A.A., 2020. Coastal Hazards System: A Probabilistic Coastal Hazard Analysis Framework. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1211-1216. Coconut Creek (Florida), ISSN 0749-0208.Coastal hazards such as storm surge, waves, currents, wind, and rainfall associated with extratropical and tropical cyclones (e.g., hurricanes) can have devastating effects and threaten the lives of millions of people living along the world's coastlines. This has led to the development of the Coastal Hazards System (CHS), an ambitious program with the primary goal of quantifying extreme coastal hazards due to both tropical and extratropical cyclones. The CHS currently covers all U.S. hurricane-prone coastlines along the Gulf of Mexico, the Atlantic seaboard, Puerto Rico, and the U.S. Virgin Islands, as well as regions affected only by extratropical storms like the Great Lakes. The Probabilistic Coastal Hazard Analysis (PCHA) is an innovative statistical and probabilistic framework that serves as the foundation of the CHS. This framework includes comprehensive characterization of storm climatology, high-resolution numerical modeling, and advanced joint probability analysis of atmospheric forcing and primary storm responses, including associated aleatory and epistemic uncertainties. New PCHA advancements overcome limitations of previous joint probability methods by integrating meta-Gaussian copula for the computation of storm probabilities, spatially-varying bias and uncertainty quantification, and Gaussian process metamodel (GPM) based on existing CHS synthetic tropical cyclones. GPM emulates the response of computationally-expensive hydrodynamic models and enables the generation of augmented tropical cyclone suites, consisting of up to millions of storms, for optimal coverage of the parameter and probability spaces. The CHS also includes a database and a web-based data mining and visualization system for public distribution of high-fidelity probabilistic, atmospheric and hydrodynamic modeling results. PCHA results are distributed along with the corresponding metadata, in self-describing data formats for easy and efficient use by engineers, planners, economists, emergency managers, and researchers.

This study examines the variation in tropical cyclone (TC) intensity for different phases of the El Niño–Southern Oscillation (ENSO) phenomenon in the Fiji, Samoa, and Tonga (FST) region. The variation in TC intensity is inferred from the accumulated cyclone energy (ACE), which is constructed from the 6-hourly Joint Typhoon Warning Center best-track data for the period 1985–2006. Overall, results suggest that ACE in the FST region is considerably influenced by the ENSO signal. A substantial contribution to this ENSO signal in ACE comes from the region equatorward of 15°S where TC numbers, lifetime, and intensity all play a significant role. However, the ACE–ENSO relationship weakens substantially poleward of 15°S where large-scale environmental variables affecting TC intensity are found to be less favorable during El Niño years than during La Niña years; in the region equatorward of 15°S, the reverse is true. Therefore, TCs entering this region poleward of 15°S are able to sustain their intensity for a longer period of time during La Niña years as opposed to TCs entering the region during El Niño years, when they decay more rapidly.

Earth's global climate system is vast, complex, and intricately interrelated. Many areas are influenced by global-scale phenomena, including the "triple dip" La Niña conditions that

Future changes in extreme precipitation over the San Francisco Bay Area: Dependence on atmospheric river and extratropical cyclone events

The synoptic structure of two case studies of heavy “spillover” or leeside precipitation—1–2 January 1997 and 30–31 December 2005—that resulted in Truckee River flooding are analyzed over the North Pacific beginning approximately 7 days prior to the events. Several sequential cyclone-scale systems are tracked across the North Pacific, culminating in the strengthening and elongation of a polar jet stream’s deep exit region over northern California and Nevada. These extratropical cyclones separate extremely cold air from Siberia from an active intertropical convergence zone with broad mesoscale convective systems and tropical cyclones. The development of moisture surges resulting in leeside flooding precipitation over the Sierra Nevada is coupled to adjustments within the last wave in the sequence of cyclone waves. Stage I of the process occurs as the final wave moves across the Pacific and its polar jet streak becomes very long, thus traversing much of the eastern Pacific. Stage II involves the development of a low-level return branch circulation [low-level jet (LLJ)] within the exit region of the final cyclone scale wave. Stage III is associated with the low-level jet’s convergence under the upper-level divergence within the left exit region, which results in upward vertical motions, dynamic destabilization, and the development of mesoscale convective systems (MCSs). Stage IV is forced by the latent heating and subsynoptic-scale ridging caused by each MCS, which results in a region of diabatic isallobaric accelerations downstream from the MCS-induced mesoridge. During stage IV the convectively induced accelerating flow, well to the southeast of the upper-level jet core, organizes a midlevel jet and plume of moisture or midlevel atmospheric river, which is above and frequently out of phase with (e.g., southeast of) the low-level atmospheric river described in Ralph et al. ahead of the surface cold front. Stage V occurs as the final sequential midlevel river arrives over the Sierra Nevada. It phases with the low-level river, allowing upslope and midlevel moisture advection, thus creating a highly concentrated moist plume extending from near 700 to nearly 500 hPa, which subsequently advects moisture over the terrain. When simulations are performed without upstream convective heating, the horizontal moisture fluxes over the Sierra Nevada are reduced by ∼30%, indicating the importance of convection in organizing the midlevel atmospheric rivers. The convective heating acts to accelerate the midlevel jet flow and create the secondary atmospheric river between ∼500 and 700 hPa near the 305-K isentropic surface. This midlevel moisture surge slopes forward with height and transports warm moist air over the Sierra Nevada to typically rain shadowed regions on the lee side of the range. Both observationally generated and model-generated back trajectories confirm the importance of this convectively forced rapid lifting process over the North Pacific west of the California coast ∼12 h and ∼1200 km upstream prior to heavy leeside spillover precipitation over the Sierra Nevada.

<p>We will first examine the skill of probabilistic tropical cyclone (TC) occurrence and intensity (ACE - accumulated cyclone energy) predictions in the Subseasonal to Seasonal (S2S) dataset. We show that some of the models in the S2S dataset have skill in predicting TC occurrence 4 weeks in advance. In contrast, only one of the models (ECMWF) has skill in predicting the anomaly of TC occurrence from the seasonal climatology beyond week 1. For models with significant mean biases, calibrating the forecast can improve the models’ prediction skill. In contrast, for models with small mean biases, calibration does not guarantee an improvement in model skill as measured by the Brier Skill Score. </p><p>We then focus only on the ECMWF model and using cluster analysis examine the sensitivity of the North Atlantic TC tracks biases to various factors, such as model resolution, lead time, and tracking. We also explore how well the ECMWF North Atlantic TC model tracks in each cluster simulate the known response to climate modes, such as ENSO and MJO. By applying simple bias corrections to each cluster of Atlantic TC tracks, we examine if we can improve the model skill in landfall prediction in the US and Caribbean.</p>

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 36:1-16 (2008) - DOI: https://doi.org/10.3354/cr00732 Regional climate model simulations of North Atlantic cyclones: frequency and intensity changes Tido Semmler1,*, Saji Varghese2, Ray McGrath1, Paul Nolan3, Shiyu Wang1, Peter Lynch3, Colin O’Dowd2 1Met Eireann, Glasnevin Hill, Dublin 9, Ireland 2National University of Ireland, Galway, University Road, Galway, Ireland 3University College Dublin, Belfield, Dublin 4, Ireland *Email: tido.semmler@met.ie ABSTRACT: Frequency and intensity of cyclones over the North Atlantic are investigated using 2 data sets from simulations with the Rossby Centre regional climate model RCA3. The model domain comprises large parts of the North Atlantic and the adjacent continents. RCA3 is driven by ECHAM5-OM1 general circulation model data for May to December from 1985 to 2000 and May to December from 2085 to 2100 assuming the SRES-A2 emission scenario. We apply an objective algorithm to identify and track tropical and extratropical cyclones, as well as extratropical transition. The simulation indicates increase in the count of strong hurricanes and extratropical cyclones. Contrasting, and generally weaker, changes are seen for the less extreme events. Decreases of 18% in the count of extratropical cyclones and 13% in the count of tropical cyclones with wind speeds of ≥18 m s-1 can be found. Furthermore, there is a pronounced shift in the tracks of hurricanes and their extratropical transition in November and December—more hurricanes are seen over the Gulf of Mexico, the Caribbean Sea and the western Sargasso Sea and less over the southern North Atlantic. KEY WORDS: Climate change · Tropical cyclone · Extratropical cyclone · Regional climate model · North Atlantic · Sea surface temperature · Static stability Full text in pdf format NextCite this article as: Semmler T, Varghese S, McGrath R, Nolan P, Wang S, Lynch P, O’Dowd C (2008) Regional climate model simulations of North Atlantic cyclones: frequency and intensity changes. Clim Res 36:1-16. https://doi.org/10.3354/cr00732 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 36, No. 1. Online publication date: March 13, 2008 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2008 Inter-Research.

The current study explores the relationship between solar variability and tropical cyclone (TC) activity using sunspot number (SSN) and TC best‐track data as respective proxies. We have considered six regions of the globe, for example, EP: Eastern Pacific, NA: North Atlantic, NI: North Indian, SI: South Indian, SP: South Pacific, and WP: Western Pacific. The results show strong anti‐correlation between yearly TC activity and yearly SSN while considering their 11‐year moving averages. This behavior is consistent for TC counts as well as accumulated cyclone energy. However, this is true only for the North Atlantic region. Overall, when we consider all regions together, more TCs (in terms of counts) are observed during lower solar activity periods (SSN < 50) as compared to higher solar activity conditions (SSN > 100). However, the yearly rates remain more or less similar. On the other hand, extreme TC events with a maximum wind speed of 137 knots and higher (category 5) are most likely to occur during the declining phase of a solar cycle and least likely to occur during the ascending phase or the maximum phase. Although solar activity levels are similar during the declining and ascending phases, the yearly occurrence rate is nearly double in the declining phase (1.123) as compared to that in the ascending phase (0.625).

The stable oxygen isotope ratio (δ18O) measured in ice cores is widely used to reconstruct past climate variability on short and long timescales. Among synoptic processes, atmospheric rivers (ARs) play a key role in the poleward transport of moisture. ARs are long, narrow corridors of intense horizontal water vapour transport, typically associated with extratropical cyclones. They convey large amounts of moisture from distant, often low-latitude source regions together with warm air advection, thereby introducing a distinct isotopic signature into precipitation. Through snowfall, the isotopic composition of atmospheric water vapour is recorded in snow and ultimately preserved in ice cores. While several studies have examined the influence of ARs on δ18O variability in Antarctic ice cores, a comparable assessment for Greenland remains more limited until now.Here, we investigate the imprint of ARs on δ18O variability in Greenland ice cores using virtual firn cores (VFCs) derived from a new high-resolution (0.5°) simulation performed with the isotope-enabled atmospheric general circulation model ECHAM6-wiso nudged to ERA5 reanalyses. VFCs are generated for the Renland Ice Cap (RECAP) and Southeastern Dome (SED) sites and evaluated against their corresponding very high-resolution measured δ18O records.Our results show that ARs do not fundamentally change the δ18O variability. However, they exert a pronounced influence on seasonal and subseasonal δ18O variations during periods when AR-related snowfall contributes a substantial fraction of total precipitation. On the subseasonal timescale, individual AR events are found to increase δ18O values by approximately 3‰ on average, with extreme cases reaching up to 5‰.

An empirical approach for analyzing tropical cyclone climate is presented. The approach uses lifetime-maximum wind speed and cyclone frequency to induce two orthogonal variables labeled “activity” and “efficiency of intensity”. The paired variations of activity and efficiency of intensity along with the opponent variations of frequency and intensity configure a framework for evaluating tropical cyclone climate. Although cyclone activity as defined in this framework is highly correlated with the commonly used exponent indices like accumulated cyclone energy, it does not contain cyclone duration. Empirical quantiles are used to determine threshold intensity levels, and variant year ranges are used to find consistent trends in tropical cyclone climatology. In the western North Pacific, cyclone activity is decreasing despite increases in lifetime-maximum intensity. This is due to overwhelming decreases in cyclone frequency. These changes are also explained by an increasing efficiency of intensity. The North Atlantic shows different behavior. Cyclone activity is increasing due to increasing frequency and, to a lesser extent, increasing intensity. These changes are also explained by a decreasing efficiency of intensity. Tropical cyclone trends over the North Atlantic basin are more consistent over different year ranges than tropical cyclone trends over the western North Pacific.

Future changes in extratropical cyclones (ETCs), their moisture transport, and their connection to atmospheric rivers (ARs) remain uncertain. Here, using downscaled simulations from the Community Earth System Model version 2 under the high-emissions scenario SSP5-8.5, we show that moisture uptake associated with intense North Atlantic ETCs will increase by ~14.5%, or ~3.29% per Kelvin of global warming by the end of this century. Subregional analysis revealed greater increases during the most intense cyclone stages, with changes of 52.1% (11.8% K−1) in the eastern North Atlantic, 33.4% (7.6% K−1) in the western North Atlantic, and 29.1% (6.6% K−1) in the northern North Atlantic. Rather than a consistent increase within existing climatological source regions, the moisture origin exhibits a geographic shift, likely linked with changes in storm-track pathways and ocean circulation under warming. Using a novel method to couple ETC moisture sources with ARs, we demonstrate that while this coupling continues to be a defining characteristic at the basin scale, the strength of their association is projected to weaken. Historical differences between low- and fully associated ETCs, particularly in terms of moisture sources and proximity to the AR axis, diminish and lose significance in a warming climate.

The potential use of the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) for downscaling seasonal tropical cyclone (TC) activity was analyzed here. The NCEP RSM with horizontal resolution of 50 km, was used to downscale the ECHAM4.5 Atmospheric General Circulation Model (AGCM) simulations forced with observed sea surface temperature (SST) over the western North Pacific. An ensemble of ten runs for June–November 1994 and 1998 was studied. The representation of the TCs is much improved compared to the low‐resolution forcing AGCM, but the TCs are not as intense as observed ones, as the RSM horizontal resolution is not sufficiently high. The large‐scale fields of the RSM are examined and compared to both the AGCM and the European Centre for Medium‐Range Weather Forecasts (ECMWF) reanalysis. The large‐scale fields of RSM characteristics are in general similar to those of the reanalysis. Various properties of the TCs in the RSM are also examined such as first positions, tracks, accumulated cyclone energy (ACE) and duration. While the RSM does not reproduce the higher number of TCs in 1994 than in 1998, other measures of TC activity (ACE, number of cyclone days) in the RSM are higher in 1994 than in 1998. Copyright © 2006 Royal Meteorological Society.

The global tropical cyclone (TC) number has historically been relatively constant from year‐to‐year, however, the reason remains unknown. Furthermore, climate projections are inconclusive regarding future global TC frequency changes. Here, we investigated years in which observed global TC activity deviated from the mean and potential links to ocean drivers from 1980 to 2021. We found that the annual global number of named storm days and accumulated cyclone energy (ACE) were significantly linked with El Niño–Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM). La Niña and positive AMM are associated with the bottom percentiles of both TC metrics, and vice versa for El Niño and negative AMM. The ENSO Longitude Index explains variability in annual global named storm days and ACE as well as the Niño 3.4 index. This research reveals that reliable future projections of ENSO are necessary, but not sufficient, to understand future changes in global TC frequency.