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Richard B. Bagley and Craig B. Clements

Abstract

The second largest fire shelter deployment in U.S. history occurred in August 2003 during the Devil Fire, which was burning in a remote and rugged region of the San Francisco Bay Area, when relative humidity abruptly dropped in the middle of the night, causing rapid fire growth. Nocturnal drying events in the higher elevations along California’s central coast are a unique phenomenon that poses a great risk to wildland firefighters. Single-digit relative humidity with dewpoints below −25°C is not uncommon during summer nights in this region. To provide the fire management community with knowledge of these hazardous conditions, an event criterion was established to develop a climatology of nocturnal drying and to investigate the synoptic patterns associated with these events. A lower-tropospheric source region of dry air was found over the northeastern Pacific Ocean corresponding to an area of maximum low-level divergence and associated subsidence. This dry air forms above a marine inversion and advects inland overnight with the marine layer and immerses higher-elevation terrain with warm and dry air. An average of 15–20 nocturnal drying events per year occur in elevations greater than 700 m in the San Francisco Bay Area, and their characteristics are highly variable, making them a challenge to forecast.

Open access
Tianyi Wang and Tim Li

Abstract

The diversity of the Madden–Julian oscillation (MJO) in terms of its maximum intensity, zonal extent, and phase speed was explored using a cluster analysis method. The zonal extent is found to be significantly correlated to the phase speed. A longer zonal extent is often associated with a faster phase speed. The diversities of zonal extent and speed are connected with distinctive interannual sea surface temperature anomaly (SSTA) distributions and associated moisture and circulation patterns over the equatorial Pacific. An El Niño–like background SSTA leads to enhanced precipitation over the central Pacific, allowing a stronger vertically overturning circulation to the east of the MJO. This promotes both a larger east–west asymmetry of column-integrated moist static energy (MSE) tendency and a greater boundary layer moisture leading, serving as potential causes of the faster phase speed. The El Niño–like SSTA also favors the MJOs intruding farther into the Pacific, causing a larger zonal extent. The intensity diversity is associated with the interannual SSTA over the Maritime Continent and background moisture condition over the tropical Indian Ocean. An observed warm SSTA over the Maritime Continent excites a local Walker cell with a subsidence over the Indian Ocean, which could decrease the background moisture, weakening the MJO intensity. The intensity difference between strong and weak events would be amplified due to distinct intensity growth speed. The faster intensity growth of a strong MJO is attributed to a greater longwave radiative heating and a greater surface latent heat flux, both of which contribute to a greater total time change rate of the column-integrated MSE.

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M. Hagman, G. Svensson, and W. M. Angevine

Abstract

The Swedish Armed Forces configuration of the Weather Research and Forecasting (WRF) Model has problems in forecasting low clouds in stably stratified conditions when the ground is covered by snow. Reforecasts for January and February 2018, together with observations from Sodankylä in northern Finland, are analyzed to find the cause. The investigation is done iteratively between the single-column model (SCM), applied at Sodankylä, and the full 3D version. Our experiments show that the forecast error arises due to inadequate initialization of stratocumulus (Sc) clouds in WRF using the ECMWF global model, Integrated Forecasting System (IFS). By including bulk liquid water and bulk ice water content, from IFS in the initial profile, the downwelling longwave radiation increases and prevents the near-surface temperature from dropping abnormally. This, in turn, prevents artificial clouds from forming at the first model level. When no clouds are present in the IFS initial profile, the Sc clouds can be initialized using information from the observed vertical profiles. Generally, initialization of Sc clouds in WRF improves the forecast substantially.

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Jonathan D. Beverley, Matthew Collins, F. Hugo Lambert, and Robin Chadwick

Abstract

El Niño–Southern Oscillation (ENSO) is the leading mode of interannual climate variability, and it exerts a strong influence on many remote regions of the world, for example in northern North America. Here, we examine future changes to the positive-phase ENSO teleconnection to the North Pacific/North America sector and investigate the mechanisms involved. We find that the positive temperature anomalies over Alaska and northern North America that are associated with an El Niño event in the present day are much weaker, or of the opposite sign, in the CMIP6 abrupt 4×CO2 experiments for almost all models (22 out of 26, of which 15 have statistically significant differences). This is largely related to changes to the anomalous circulation over the North Pacific, rather than differences in the equator-to-pole temperature gradient. Using a barotropic model, run with different background circulation basic states and Rossby wave source forcing patterns from the individual CMIP6 models, we find that changes to the forcing from the equatorial central Pacific precipitation anomalies are more important than changes in the global basic state background circulation. By further decomposing this forcing change into changes associated with the longitude and magnitude of ENSO precipitation anomalies, we demonstrate that the projected overall eastward shift of ENSO precipitation is the main driver of the temperature teleconnection change, rather than the increase in magnitude of El Niño precipitation anomalies, which is nevertheless seen in the majority of models.

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Yawen Shao, Quan J. Wang, Andrew Schepen, and Dongryeol Ryu

Abstract

For managing climate variability and adapting to climate change, seasonal forecasts are widely produced to inform decision-making. However, seasonal forecasts from global climate models are found to poorly reproduce temperature trends in observations. Furthermore, this problem is not addressed by existing forecast postprocessing methods that are needed to remedy biases and uncertainties in model forecasts. The inability of the forecasts to reproduce the trends severely undermines user confidence in the forecasts. In our previous work, we proposed a new statistical postprocessing model that counteracted departures in trends of model forecasts from observations. Here, we further extend this trend-aware forecast postprocessing methodology to carefully treat the trend uncertainty associated with the sampling variability due to limited data records. This new methodology is validated on forecasting seasonal averages of daily maximum and minimum temperatures for Australia based on the SEAS5 climate model of the European Centre for Medium-Range Weather Forecasts. The resulting postprocessed forecasts are shown to have proper trends embedded, leading to greater accuracy in regions with significant trends. The application of this new forecast postprocessing is expected to boost user confidence in seasonal climate forecasts.

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Arianna M. Varuolo-Clarke, Jason E. Smerdon, A. Park Williams, and Richard Seager

Abstract

Southeastern South America (SESA; encompassing Paraguay, southern Brazil, Uruguay, and northern Argentina) experienced a 27% increase in austral summer precipitation from 1902 to 2019, one of the largest observed trends in seasonal precipitation globally. Previous research identifies Atlantic multidecadal variability and anthropogenic forcing from stratospheric ozone depletion and greenhouse gas emissions as key factors contributing to the positive precipitation trends in SESA. We analyze multimodel ensemble simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) and find that not only do Earth system models simulate positive SESA precipitation trends that are much weaker over the historical interval, but some models persistently simulate negative SESA precipitation trends under historical forcings. Similarly, 16-member ensembles from two atmospheric models forced with observed historical sea surface temperatures never simulate precipitation trends that even reach the lower bound of the observed trend’s range of uncertainty. Moreover, while future twenty-first-century projections from CMIP6 yield positive ensemble mean precipitation trends over SESA that grow with increasing greenhouse gas emissions, the mean forced response never exceeds the observed historical trend. Preindustrial control runs from CMIP6 indicate that some models do occasionally simulate centennial-scale trends in SESA that fall within the observational range, but most models do not. Results point to significant uncertainties in the attribution of anthropogenically forced influences on the observed increases in precipitation over SESA while also suggesting that internal decadal-to-centennial variability of unknown origin and not present in state-of-the-art models may have also played a large role in generating the twentieth-to-twenty-first-century SESA precipitation trend.

Open access
Michael A. Spall

Abstract

The frequency and latitudinal dependence of the midlatitude wind-driven meridional overturning circulation (MOC) is studied using theory and linear and nonlinear applications of a quasigeostrophic numerical model. Wind forcing is varied either by changing the strength of the wind or by shifting the meridional location of the wind stress curl pattern. At forcing periods of less than the first-mode baroclinic Rossby wave basin crossing time scale, the linear response in the middepth and deep ocean is in phase and opposite to the Ekman transport. For forcing periods that are close to the Rossby wave basin crossing time scale, the upper and deep MOC are enhanced, and the middepth MOC becomes phase shifted, relative to the Ekman transport. At longer forcing periods the deep MOC weakens and the middepth MOC increases, but eventually for long enough forcing periods (decadal) the entire wind-driven MOC spins down. Nonlinearities and mesoscale eddies are found to be important in two ways. First, baroclinic instability causes the middepth MOC to weaken, lose correlation with the Ekman transport, and lose correlation with the MOC in the opposite gyre. Second, eddy thickness fluxes extend the MOC beyond the latitudes of direct wind forcing. These results are consistent with several recent studies describing the four-dimensional structure of the MOC in the North Atlantic Ocean.

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Huijun Huang, Jinnan Yuan, Guanhuan Wen, Xueyan Bi, Ling Huang, and Mingsen Zhou

Abstract

Tropical depressions formed over the South China Sea usually produce severe flooding and wind damage when they develop into a storm and make landfall. To provide an early warning, forecasters should know when, and if, a tropical depression will develop into a tropical storm. To better understand and predict such development, we examine the dynamic and thermodynamic variables of 74 tropical depressions over the South China Sea, 52 of which developed into storms, hereafter “developing,” with the remaining being classified as “nondeveloping.” Using the National Centers for Environmental Prediction Final (NCEP FNL) data, verified with ECMWF forecast data, we examine the dynamic and thermodynamic statistics that characterize these tropical cyclones. Based on these characteristics, we propose seven criteria to determine whether a tropical depression will develop. Five had been used before, but two new criteria are also found to be useful. These two are associated with the diabatic heating rate and help to determine whether a tropical cyclone diurnal cycle exists and whether the convection system remains intact in the center: 1) presence of a regular diurnal variation of the diabatic heating rate at the center and 2) occurrence of specific peaks in the radiative-heating profile. We test all seven criteria on all tropical depression cases in 2018/19 before the system developed or decayed, showing that these criteria can help to operationally identify whether or not a tropical depression develops into a tropical storm with an average lead time of 36.6 h.

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Hong-Chang Ren, Jinqing Zuo, and Weijing Li

Abstract

The interannual variability of boreal summer sea surface temperature (SST) in the tropical Atlantic displays two dominant modes, the Atlantic zonal mode highlighting SST variations in the equatorial–southern tropical Atlantic (ESTA) region and the northern tropical Atlantic (NTA) mode focusing on SST fluctuations in the NTA region except in the Gulf of Guinea. Observational evidence indicates that both the boreal summer ESTA and NTA warming are accompanied by a pair of anomalous low-level anticyclones over the western tropical Pacific, and the NTA-related anticyclone is more obvious than the ESTA-related one. Both atmosphere-only and partially coupled experiments conducted with the Community Earth System Model version 1.2 support the observed NTA–Pacific teleconnection. In contrast, the ESTA-induced atmospheric circulation response is negligible over the tropical Pacific in the atmosphere-only experiments, and although the response becomes stronger in the partially coupled experiments, obvious differences still exist between the simulations and observation. The ESTA-induced atmospheric circulation response features an anomalous low-level cyclone over the western tropical Pacific in the partially coupled experiments, opposite to its observed counterpart. It is found that the ESTA warming coincides with significantly La Niña–like SST anomalies in the central–eastern equatorial Pacific, the influence of which on the tropical atmospheric circulation is opposite to that of the ESTA warming, and therefore contributes to difference between the ESTA-related simulations and observation. Moreover, the cold climatological mean SST in the ESTA region is unfavorable to enhancing the ESTA–Pacific teleconnection during boreal summer.

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Aaron J. Hill, Christopher C. Weiss, and David C. Dowell

Abstract

Ensemble forecasts are generated with and without the assimilation of near-surface observations from a portable, mesoscale network of StickNet platforms during the Verification of the Origins of Rotation in Tornadoes Experiment–Southeast (VORTEX-SE). Four VORTEX-SE intensive observing periods are selected to evaluate the impact of StickNet observations on forecasts and predictability of deep convection within the Southeast United States. StickNet observations are assimilated with an experimental version of the High-Resolution Rapid Refresh Ensemble (HRRRE) in one experiment, and withheld in a control forecast experiment. Overall, StickNet observations are found to effectively reduce mesoscale analysis and forecast errors of temperature and dewpoint. Differences in ensemble analyses between the two parallel experiments are maximized near the StickNet array and then either propagate away with the mean low-level flow through the forecast period or remain quasi-stationary, reducing local analysis biases. Forecast errors of temperature and dewpoint exhibit periods of improvement and degradation relative to the control forecast, and error increases are largely driven on the storm scale. Convection predictability, measured through subjective evaluation and objective verification of forecast updraft helicity, is driven more by when forecasts are initialized (i.e., more data assimilation cycles with conventional observations) rather than the inclusion of StickNet observations in data assimilation. It is hypothesized that the full impact of assimilating these data is not realized in part due to poor sampling of forecast sensitive regions by the StickNet platforms, as identified through ensemble sensitivity analysis.

Open access