Browse

You are looking at 1 - 10 of 119,159 items for

  • Refine by Access: All Content x
Clear All
Evan S. Bentley, Richard L. Thompson, Barry R. Bowers, Justin G. Gibbs, and Steven E. Nelson

Abstract

Previous work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–18) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance. Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment, which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1 n mi; 1 n mi = 1.852 km) circulations in a poor (STP = 0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.

Restricted access
Jason M. English, David D. Turner, Trevor I. Alcott, William R. Moninger, Janice L. Bytheway, Robert Cifelli, and Melinda Marquis

Abstract

Improved forecasts of atmospheric river (AR) events, which provide up to half the annual precipitation in California, may reduce impacts to water supply, lives, and property. We evaluate quantitative precipitation forecasts (QPF) from the High-Resolution Rapid Refresh model version 3 (HRRRv3) and version 4 (HRRRv4) for five AR events that occurred in February–March 2019 and compare them to quantitative precipitation estimates (QPE) from Stage IV and Mesonet products. Both HRRR versions forecast spatial patterns of precipitation reasonably well, but are drier than QPE products in the Bay Area and wetter in the Sierra Nevada range. The HRRR dry bias in the Bay Area may be related to biases in the model temperature profile, while integrated water vapor (IWV), wind speed, and wind direction compare reasonably well. In the Sierra Nevada range, QPE and QPF agree well at temperatures above freezing. Below freezing, the discrepancies are due in part to errors in the QPE products, which are known to underestimate frozen precipitation in mountainous terrain. HRRR frozen QPF accuracy is difficult to quantify, but the model does have wind speed and wind direction biases near the Sierra Nevada range. HRRRv4 is overall more accurate than HRRRv3, likely due to data assimilation improvements, and possibly physics improvements. Applying a neighborhood maximum method impacted performance metrics, but did not alter general conclusions, suggesting closest gridbox evaluations may be adequate for these types of events. Improvements to QPF in the Bay Area and QPE/QPF in the Sierra Nevada range would be particularly useful to provide better understanding of AR events.

Restricted access
Jing Zhang, Jie Feng, Hong Li, Yuejian Zhu, Xiefei Zhi, and Feng Zhang

Abstract

Operational and research applications generally use the consensus approach for forecasting the track and intensity of tropical cyclones (TCs) due to the spatial displacement of the TC location and structure in ensemble member forecasts. This approach simply averages the location and intensity information for TCs in individual ensemble members, which is distinct from the traditional pointwise arithmetic mean (AM) method for ensemble forecast fields. The consensus approach, despite having improved skills relative to the AM in predicting the TC intensity, cannot provide forecasts of the TC spatial structure. We introduced a unified TC ensemble mean forecast based on the feature-oriented mean (FM) method to overcome the inconsistency between the AM and consensus forecasts. FM spatially aligns the TC-related features in each ensemble field to their geographical mean positions before the amplitude of their features is averaged. We select 219 TC forecast samples during the summer of 2017 for an overall evaluation of the FM performance. The results show that the TC track consensus forecasts can differ from AM track forecasts by hundreds of kilometers at long lead times. AM also gives a systematic and statistically significant underestimation of the TC intensity compared with the consensus forecast. By contrast, FM has a very similar TC track and intensity forecast skill to the consensus approach. FM can also provide the corresponding ensemble mean forecasts of the TC spatial structure that are significantly more accurate than AM for the low- and upper-level circulation in TCs. The FM method has the potential to serve as a valuable unified ensemble mean approach for the TC prediction.

Open access
Pengfei Shi, Jiangyuan Zeng, Kun-Shan Chen, Hongliang Ma, Haiyun Bi, and Chenyang Cui

Abstract

The Tibetan Plateau (TP), known as the “Third Pole,” is a climate-sensitive and ecology-fragile region. In this study, the spatiotemporal trends of soil moisture (SM) and vegetation were analyzed using satellite-based ESA CCI SM and MODIS LAI data, respectively, in the growing season during the last 20 years (2000–19) over the TP covering diverse climate zones. The climatic drivers (precipitation and air temperature) of SM and LAI variations were fully investigated by using both ERA5 reanalysis and observation-based gridded data. The results reveal the TP is generally wetting and significantly greening in the last 20 years. The SM with significant increasing trend accounts for 21.80% (fraction of grid cells) of the TP, and is about twice of the SM with significant decreasing trend (10.19%), while more than half of the TP (58.21%) exhibits significant increasing trend of LAI. Though the responses of SM and LAI to climatic factors are spatially heterogeneous, precipitation is the dominant driver of SM variation with 48.36% (ERA5) and 32.51% (observation-based) precipitation data showing the strongest significant positive partial correlation with SM. Temperature rise largely explains the vegetation greening, though precipitation also plays an important role in vegetation growth in arid and semiarid zones. The combined trend of SM and LAI indicates the TP is mainly composed of wetting and greening areas, followed by drying and greening regions. The change rate of SM is negative at low altitudes and becomes positive as altitude increases, while the LAI value and its change rate decrease as altitude increases.

Restricted access
Emily Bercos-Hickey, Christina M. Patricola, and William A. Gallus Jr

Abstract

The impact of climate change on severe storms and tornadoes remains uncertain, largely owing to inconsistencies in observational data and limitations of climate models. We performed ensembles of convection-permitting climate model simulations to examine how three tornadic storms would change if similar events were to occur in pre-industrial and future climates. The choice of events includes winter, nocturnal, and spring tornadic storms to provide insight into how the timing and seasonality of storms may affect their response to climate change. Updraft helicity (UH), convective available potential energy (CAPE), storm-relative helicity (SRH), and convective inhibition (CIN) were used to determine the favorability for the three tornadic storm events in the different climate states. We found that from the pre-industrial period to the present, the potential for tornadic storms decreased for the winter event and increased for the nocturnal and spring events. With future climate change, the potential for tornadic storms increased for the winter and nocturnal events in association with increased CAPE, and decreased for the spring event despite greater CAPE.

Restricted access
A. C. Sousa, L. A. Candido, and P. Satyamurty

Abstract

Mesoscale convective cloud clusters develop and organize in the form of squall lines along the coastal Amazon in the afternoon hours and propagate inland during the evening hours. The frequency, location, organization into lines, and movement of the convective systems are determined by analyzing the “precipitation features” obtained from the TRMM satellite for the period 1998–2014. The convective clusters and their alignments into Amazon coastal squall lines are more frequent from December to July, and they mostly stay within 170 km of the coastline. Their development and movement in the afternoon and evening hours of about 14 m s−1 are helped by the sea breeze. Negative phase of Atlantic dipole and La Niña combined increase the frequency of convective clusters over the coastal Amazon. Composite environmental conditions of 13 large Amazon coastal squall-line cases in April show that conditional instability increases from 0900 to 1200 LT and the wind profiles show a jet-like structure at low levels of the atmosphere. The differences in the vertical profiles of temperature and humidity between the large-squall-line composites and no-squall-line composites are weak. However, appreciable increase in the mean value of CAPE from 0900 to 1500 LT is found in the large-squall-line composite. The mean mixing ratio of the mixed layer at 0900 LT in La Niña situations is significantly larger in the large-squall-line composite. Thus, CAPE and mixed-layer mixing ratio are considered to be promising indicators of the convective activity over the coastal belt of the Amazon basin.

Restricted access
Coltin Grasmick, Bart Geerts, Xia Chu, Jeffrey R. French, and Robert M. Rauber

Abstract

Kelvin–Helmholtz (KH) waves are a frequent source of turbulence in stratiform precipitation systems over mountainous terrain. KH waves introduce large eddies into otherwise laminar flow, with updrafts and downdrafts generating small-scale turbulence. When they occur in cloud, such dynamics influence microphysical processes that impact precipitation growth and fallout. Part I of this paper used dual-Doppler, 2D wind and reflectivity measurements from an airborne cloud radar to demonstrate the occurrence of KH waves in stratiform orographic precipitation systems and identified four mechanisms for triggering KH waves. In Part II, we use similar observations to explore the effects of KH wave updrafts and turbulence on cloud microphysics. Measurements within KH wave updrafts reveal the production of liquid water in otherwise ice-dominated clouds, which can contribute to snow generation or enhancement via depositional and accretional growth. Fallstreaks beneath KH waves contain higher ice water content, composed of larger and more numerous ice particles, suggesting that KH waves and associated turbulence may also increase ice nucleation. A large-eddy simulation (LES), designed to model the microphysical response to the KH wave eddies in mixed-phase cloud, shows that depositional and accretional growth can be enhanced in KH waves, resulting in more precipitation when compared to a baseline simulation. While sublimation and evaporation occur in KH downdrafts, persistent supersaturation with respect to ice allows for a net increase in ice mass. These modeling results and observations suggest that KH waves embedded in mixed-phase stratiform clouds may increase precipitation, although the quantitative impact remains uncertain.

Restricted access
S. K. Mishra

Abstract

Structure and time evolution of the large-scale background and an embedded synoptic-scale monsoon depression and their interactions are studied. The depression formation is preceded by a cyclonic circulation around 400 hPa. The Fourier-based scale separation technique is used to isolate large (wavenumbers 0–8) and synoptic-scale (wavenumbers 12–60). The wavelength and depression center is determined objectively. The synoptic-scale depression has an average longitudinal wavelength of around 1900 km and a north–south size of 1100 km; it is most intense with a vorticity of 20.5 × 10−5 s−1 at 900 hPa. The strongest cold core of −3.0°C below 850 hPa and the above warm core of around 2.0°C are evident. The depression is tilted southwestward in the midtroposphere with no significant vertical tilt in the lower troposphere. The mean maximum intensity and upward motion over the life cycle of depression are in close agreement with the composite values. A strong cyclonic shear zone is developed in the midtroposphere preceding the depression. The necessary condition for barotropic (baroclinic) instability is satisfied in the midtroposphere (boundary layer). Strong northward transport of momentum by the depression against the southward shear is found. The strong growth of the MD in the lower troposphere is due to downward transfer of excess energy gained in the midtroposphere from the barotropic energy conversion and east–west direct thermal circulation as the vertical energy flux. The baroclinic interaction contributes to the maintenance of the cold core in the lower troposphere. The diabatic heating rate is computed and its role in the genesis and growth of MD is investigated.

Restricted access
Tilla Roy, Jean Baptiste Sallée, Laurent Bopp, and Nicolas Metzl

Abstract

Anthropogenic CO2-emission-induced feedbacks between the carbon cycle and the climate system perturb the efficiency of atmospheric CO2 uptake by land and ocean carbon reservoirs. The Southern Ocean is a region where these feedbacks can be largest and differ most among Earth system model projections of twenty-first-century climate change. To improve our mechanistic understanding of these feedbacks, we develop an automated procedure that tracks changes in the positions of Southern Ocean water masses and their carbon uptake. In an idealized ensemble of climate change projections, we diagnose two carbon–concentration feedbacks driven by atmospheric CO2 (due to increasing air–sea CO2 partial pressure difference, dpCO2, and reducing carbonate buffering capacity) and two carbon–climate feedbacks driven by climate change (due to changes in the water mass surface outcrop areas and local climate impacts). Collectively these feedbacks increase the CO2 uptake by the Southern Ocean and account for almost one-fourth of the global uptake of CO2 emissions. The increase in CO2 uptake is primarily dpCO2 driven, with Antarctic Intermediate Waters making the largest contribution; the remaining three feedbacks partially offset this increase (by ~25%), with maximum reductions in Subantarctic Mode Waters. The process dominating the decrease in CO2 uptake is water mass dependent: reduction in carbonate buffering capacity in Subtropical and Subantarctic Mode Waters, local climate impacts in Antarctic Intermediate Waters, and reduction in outcrop areas in Circumpolar Deep Waters and Antarctic Bottom Waters. Intermodel variability in the feedbacks is predominately dpCO2 driven and should be a focus of efforts to constrain projection uncertainty.

Open access
Lei Zhang, Weiqing Han, Gerald A. Meehl, Aixue Hu, Nan Rosenbloom, Toshiaki Shinoda, and Michael J. McPhaden

Abstract

Understanding the impact of the Indian Ocean dipole (IOD) on El Niño–Southern Oscillation (ENSO) is important for climate prediction. By analyzing observational data and performing Indian and Pacific Ocean pacemaker experiments using a state-of-the-art climate model, we find that a positive IOD (pIOD) can favor both cold and warm sea surface temperature anomalies (SSTA) in the tropical Pacific, in contrast to the previously identified pIOD–El Niño connection. The diverse impacts of the pIOD on ENSO are related to SSTA in the Seychelles–Chagos thermocline ridge (SCTR; 60°–85°E, 7°–15°S) as part of the warm pole of the pIOD. Specifically, a pIOD with SCTR warming can cause warm SSTA in the southeastern Indian Ocean, which induces La Niña–like conditions in the tropical Pacific through interbasin interaction processes associated with a recently identified climate phenomenon dubbed the “warm pool dipole.” This study identifies a new pIOD–ENSO relationship and examines the associated mechanisms.

Restricted access