ALBERT

Description: 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 (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.

Description: This study compares the spread in climatological tropical cyclone (TC) precipitation across eight different reanalysis datasets: NCEP-CFSR, ERA-20C, ERA-40, ERA5, ERA-Interim, JRA-55, MERRA-2, and NOAA-20C. TC precipitation is assigned using manual tracking via a fixed 500-km radius from each TC center. The reanalyses capture similar general spatial patterns of TC precipitation and TC precipitation fraction, defined as the fraction of annual precipitation assigned to TCs, and the spread in TC precipitation is larger than the spread in total precipitation across reanalyses. The spread in TC precipitation relative to the inter-reanalysis mean TC precipitation, or relative spread, is larger in the east Pacific than in the west Pacific. Partitioned by reanalysis intensity, the largest relative spread across reanalyses in TC precipitation is from high-intensity TCs. In comparison with satellite observations, reanalyses show lower climatological mean annual TC precipitation over most areas. A comparison of area-averaged precipitation rate in TCs composited over reanalysis intensity shows the spread across reanalyses is larger for higher intensity TCs. Testing the sensitivity of TC precipitation assignment to tracking method shows that climatological mean annual TC precipitation is systematically larger when assigned via manual tracking versus objective tracking. However, this tendency is minimized when TC precipitation is normalized by TC density. Overall, TC precipitation in reanalyses is affected by not only horizontal output resolution or any TC preprocessing, but also data assimilation and parameterization schemes. The results indicate that improvements in the representation of TCs and their precipitation in reanalyses are needed to improve overall precipitation.

Description: The canonical tropospheric response to a weakening of the stratospheric vortex—an equatorward shift of the eddy-driven jet—is mostly limited to the North Atlantic following sudden stratospheric warmings (SSWs). A coherent change in the Pacific eddy-driven jet is notably absent. Why is this so? Using daily reanalysis data, we show that air–sea interactions over the North Pacific are responsible for the basin-asymmetric response to SSWs. Prior to the onset of some SSWs, their tropospheric precursors produce a dipolar SST pattern in the North Pacific, which then persists as the stratospheric polar vortex breaks down following the onset of the SSW. By reinforcing the lower-tropospheric baroclinicity, the dipolar SST pattern helps sustain the generation of baroclinic eddies, strengthening the near-surface Pacific eddy-driven jet and maintaining its near-climatological-mean state. This prevents the jet from being perturbed by the downward influence of the stratospheric anomalies. As a result, these SSWs exhibit a highly basin-asymmetric surface response with only the Atlantic eddy-driven jet shifted equatorward. For SSWs occurring without the atmospheric precursors in the North Pacific troposphere, the dipolar SST pattern is absent due to the lack of the atmospheric forcing. In the absence of the dipolar SST pattern and the resultant eddy–mean flow feedbacks, these SSWs exhibit a basin-symmetric surface response with both the Atlantic and the Pacific eddy-driven jets shifted equatorward. Our results provide an ocean–atmosphere coupled perspective on stratosphere–troposphere interaction following SSW events and have potential for improving subseasonal to seasonal forecasts for surface weather and climate.

Description: The Arctic winter sea ice cover is in retreat overlaid by large internal variability. Changes to sea ice are driven by exchange of heat, momentum, and freshwater within and between the ocean and the atmosphere. Using a combination of observations and output from the Community Earth System Model Large Ensemble, we analyze and contrast present and future drivers of the regional winter sea ice cover. Consistent with observations and previous studies, we find that for the recent decades ocean heat transport though the Barents Sea and Bering Strait is a major source of sea ice variability in the Atlantic and Pacific sectors of the Arctic, respectively. Future projections show a gradually expanding footprint of Pacific and Atlantic inflows highlighting the importance of future Atlantification and Pacification of the Arctic Ocean. While the dominant hemispheric modes of winter atmospheric circulation are only weakly connected to the sea ice, we find distinct local atmospheric circulation patterns associated with present and future regional sea ice variability in the Atlantic and Pacific sectors, consistent with heat and moisture transport from lower latitudes. Even if the total freshwater input from rivers is projected to increase substantially, its influence on simulated sea ice is small in the context of internal variability.

Description: A future projection of four extreme precipitation indices over the Indochina Peninsula and South China (INCSC) region with reference to the period 1958–2014 is conducted through the application of a multimodel ensemble approach and a rank-based weighting method. The weight of each model from phase 6 of the Coupled Model Intercomparison Project (CMIP6) is calculated depending on its historical simulation skill. Then, the weighted and unweighted ensembles are used for future projections. The results show that all four extreme precipitation indices are expected to increase over the INCSC region, both in the middle (2041–60) and at the end (2081–2100) of the twenty-first century, under three Shared Socioeconomic Pathway (SSP) scenarios. The increases in total extreme precipitation (R95p), extreme precipitation days (R95d), and the fraction of total rainfall from events exceeding the extreme precipitation threshold (R95pT) in the Indochina Peninsula are more significant than those in South China. The occurrence of extreme rainfall events may become more frequent in the future over the INCSC region, since the probability that R95pT increases is larger than 0.7 in the whole INCSC region. A comparison between the weighted and unweighted ensemble means shows that the uncertainty over South China is almost always reduced after applying the weighted scheme to future probabilistic projection, while the reductions in uncertainty over the Indochina Peninsula may depend on SSPs. The more extreme precipitation over the INCSC region in the future may be related to the larger water vapor supply and the more unstable local atmospheric stratification.

Description: Convective available potential energy (CAPE) is of strong interest in climate modeling because of its role in both severe weather and in model construction. Extreme levels of CAPE (〉2000 J kg−1) are associated with high-impact weather events, and CAPE is widely used in convective parameterizations to help determine the strength and timing of convection. However, to date few studies have systematically evaluated CAPE biases in models in a climatological context, and none have addressed bias in the high tail of CAPE distributions. This work compares CAPE distributions in ~200 000 summertime proximity soundings from four sources: the observational radiosonde network [Integrated Global Radiosonde Archive (IGRA)], 0.125° reanalyses (ERA-Interim and ERA5), and a 4-km convection-permitting regional WRF simulation driven by ERA-Interim. Both reanalyses and the WRF Model consistently show too-narrow distributions of CAPE, with the high tail (〉90th percentile) systematically biased low by up to 10% in surface-based CAPE and even more in alternate CAPE definitions. This “missing tail” corresponds to the most impacts-relevant conditions. CAPE bias in all datasets is driven by surface temperature and humidity: reanalyses and the WRF Model underpredict observed cases of extreme heat and moisture. These results suggest that reducing inaccuracies in land surface and boundary layer models is critical for accurately reproducing CAPE.

Description: The water sources and their variability responsible for the South Asian summer monsoon precipitation were analyzed using Lagrangian atmospheric water-mass trajectories. The results indicated that evaporated waters from the central and south Indian Ocean are the major contributors to the South Asian summer monsoon rainfall, followed by the contribution from the local recycling (precipitated water that evapotranspirated from the South Asian landmass), the Arabian Sea, remote sources, and the Bay of Bengal. It was also found that although the direct contribution originating from the Bay of Bengal is small, it still provides a pathway for the atmospheric water that comes from other regions. This pathway is hence only crossing over the Bay of Bengal. The outcomes further revealed that the evaporated waters originating from the central and south Indian Ocean are responsible for the net precipitation over the coastal regions of the Ganges–Brahmaputra–Meghna Delta, northeast India, Myanmar, the foothills of the Himalayas, and central-east India. Evaporated waters from the Arabian Sea are mainly contributing to the rainfall over the western coast and west-central India. Summer monsoon precipitation due to the local recycling is primarily restricted to the Indo-Gangetic plain. No recycled precipitation was observed over the mountain chain along the west coast of India (Western Ghats). The month-to-month precipitation variation over South Asia was analyzed to be linked with the Somali low-level jet variability. The interannual variability of the South Asian summer monsoon precipitation was found to be mainly controlled by the atmospheric waters that were sourced and traveled from the central and south Indian Ocean.

Description: Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s $$H^2$$ H 2 statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall, the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests.      Supplementary materials accompanying this paper appear on-line.