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Ge Song, Bohua Huang, Rongcai Ren, and Zeng-Zhen Hu

Abstract

In this article, the interannual variability of upper-ocean temperature in the equatorial Indian Ocean (IO) and its basinwide connections are investigated using 58-yr (1958–2015) comprehensive monthly mean ocean reanalysis data. Three leading modes of an empirical orthogonal function (EOF) analysis dominate the variability of upper-ocean temperature in the equatorial IO over a wide range of time scales. A coherent interannual band within the first two EOF modes identifies an oscillation between the zonally tilting thermocline across the equatorial IO in its peak phases and basinwide displacement of the equatorial thermocline in its transitional phases. Consistent with the recharge oscillation paradigm, this oscillation is inherent in the equatorial IO with a quasi-periodicity around 15 months, in which the wind-induced off-equatorial Rossby waves near 5°–10°S provide the phase-transition mechanism. This intrinsic IO oscillation provides the biennial component in the observed IOD variations. The third leading mode shows a nonlinear long-term trend of the upper-ocean temperature, including the near-surface warming along the equatorial Indian Ocean, accompanied by cooling trend in the lower thermocline originating farther south. Such vertical contrary trends may lead to an enhanced stratification in the equatorial IO.

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Annick Terpstra, Ian A. Renfrew, and Denis E. Sergeev

Abstract

Equatorward excursions of cold polar air masses into ice-free regions, so-called cold-air outbreak (CAO) events, are frequently accompanied by the development of severe mesoscale weather features. Focusing on two key regions, the Labrador Sea and the Greenland–Norwegian Seas, we apply objective detection for both CAO events and polar mesoscale cyclones to outline the temporal evolution of CAO events and quantify associated mesoscale cyclogenesis. We introduce a novel metric, the CAO depth, which incorporates both the static stability and the temperature of the air mass. The large-scale atmospheric conditions during the onset of CAO events comprise a very cold upper-level trough over the CAO region and a surface cyclone downstream. As the CAO matures, the cold air mass extends southeastward, accompanied by lower static stability and enhanced surface fluxes. Despite the nearly 20° difference in latitude, CAO events over both regions exhibit similar evolution and characteristics including surface fluxes and thermodynamic structure. About two-thirds of the identified CAO events are accompanied by polar mesoscale cyclogenesis, with the majority of mesoscale cyclones originating inside the cold air masses. Neither the duration nor the maturity of the CAO event seems relevant for mesoscale cyclogenesis. Mesoscale cyclogenesis conditions during CAO events over the Labrador Sea are warmer, moister and exhibit stronger surface latent heat fluxes than their Norwegian Sea counterparts.

Open access
Hidetaka Hirata

Abstract

We examined the climatological features of strong winds associated with extratropical cyclones around Japan during 40 seasons between November and April from 1979/80 to 2018/19 using reanalysis data. Our assessments revealed that the extratropical cyclones caused most of the strong winds around Japan (80%–90%). Notably, the contribution of explosively developing extratropical cyclones is larger (70%–80%). The strong winds are mainly related to the warm conveyor belt (WCB) and cold conveyor belt (CCB) inside the explosive cyclones. Moreover, the strong winds tend to be distributed widely over the southwestern quadrant of the cyclones. This is due to the intensification of the horizontal pressure gradient between the mature cyclones and the Siberian high extending from the Eurasian continent to Japan. We investigated the regionality of strong winds by highlighting the three areas with high frequencies of strong winds: the area around Hokkaido (i.e., the northernmost island of Japan; area A), and the areas around the Japan Sea side (area B) and the Pacific Ocean side (area C) of the main island of Japan. The features of the seasonal change in the frequency of the strong winds differ in each area, which reflects the seasonal change in the activities of the explosive cyclones. Moreover, the CCB, the head of the CCB and WCB, and the CCB and WCB bring the strong winds to areas A, B, and C, respectively. The timing of the appearance of these windstorms during the life cycles of typical cases highlighted in this study is consistent with that observed in Europe.

Open access
Hamish D. Prince, Nicolas J. Cullen, Peter B. Gibson, Jono Conway, and Daniel G. Kingston

Abstract

The occurrence of extreme precipitation events in New Zealand regularly results in devastating impacts to the local society and environment. An automated atmospheric river (AR) detection technique (ARDT) is applied to construct a climatology (1979–2019) of extreme midlatitude moisture fluxes conducive to extreme precipitation. A distinct seasonality exists in AR occurrence aligning with seasonal variations in the midlatitude jet streams. The formation of the Southern Hemisphere winter split jet enables AR occurrence to persist through all seasons in northern regions of New Zealand, while southern regions of the country exhibit a substantial (50%) reduction in AR occurrence as the polar jet shifts southward during the cold season. ARs making landfall on the western coast of New Zealand (90% of all events) are characterized by a dominant northwesterly moisture flux associated with a distinct dipole pressure anomaly, with low pressure to the southwest and high pressure to the northeast of New Zealand. Precipitation totals during AR events increase with AR rank (five-point scale) throughout the country, with the most substantial increase on the windward side of the Southern Alps (South Island). The largest events (rank 5 ARs) produce 3-day precipitation totals exceeding 1000 mm. ARs account for up to 78% of total precipitation and up to 94% of extreme precipitation on the west coast of the South Island. Assessment of the multiscale atmospheric processes associated with AR events governing extreme precipitation in the Southern Alps of New Zealand should remain a priority given their hydrological significance and impact on people and infrastructure.

Open access
Alex Schueth, Christopher Weiss, and Johannes M. L. Dahl

Abstract

The forward-flank convergence boundary (FFCB) in supercells has been well documented in many observational and modeling studies. It is theorized that the FFCB is a focal point for the baroclinic generation of vorticity. This vorticity is generally horizontal and streamwise in nature, which can then be tilted and converted to midlevel (3–6 km AGL) vertical vorticity. Previous modeling studies of supercells often show horizontal streamwise vorticity present behind the FFCB, with higher-resolution simulations resolving larger magnitudes of horizontal vorticity. Recently, studies have shown a particularly strong realization of this vorticity called the streamwise vorticity current (SVC). In this study, a tornadic supercell is simulated with the Bryan Cloud Model at 125-m horizontal grid spacing, and a coherent SVC is shown to be present. Simulated range–height indicator (RHI) data show the strongest horizontal vorticity is located on the periphery of a steady-state Kelvin–Helmholtz billow in the FFCB head. Additionally, a similar structure is found in two separate observed cases with the Texas Tech University Ka-band (TTUKa) mobile radar RHIs. Analyzing vorticity budgets for parcels in the vicinity of the FFCB head in the simulation, stretching of vorticity is the primary contributor to the strong streamwise vorticity, while baroclinic generation of vorticity plays a smaller role.

Open access
Akshay Deoras, Kieran M. R. Hunt, and Andrew G. Turner

Abstract

This study analyzes the prediction of Indian monsoon low pressure systems (LPSs) on an extended time scale of 15 days by models of the Subseasonal-to-Seasonal (S2S) prediction project. Using a feature-tracking algorithm, LPSs are identified in 11 S2S models during a common reforecast period of June–September 1999–2010, and then compared with 290 and 281 LPSs tracked in ERA-Interim and MERRA-2 reanalysis datasets. The results show that all S2S models underestimate the frequency of LPSs. They are able to represent transits, genesis, and lysis of LPSs; however, large biases are observed in the Australian Bureau of Meteorology, China Meteorological Administration (CMA), and Hydrometeorological Centre of Russia (HMCR) models. The CMA model exhibits large LPS track position error and the intensity of LPSs is overestimated (underestimated) by most models when verified against ERA-Interim (MERRA-2). The European Centre for Medium-Range Weather Forecasts and Met Office models have the best ensemble spread–error relationship for the track position and intensity, whereas the HMCR model has the worst. Most S2S models are underdispersive—more so for the intensity than the position. We find the influence of errors in the LPS simulation on the pattern of total precipitation biases in all S2S models. In most models, precipitation biases increase with forecast lead time over most of the monsoon core zone. These results demonstrate the potential for S2S models at simulating LPSs, thereby giving the possibility of improved disaster preparedness and water resources planning.

Open access
Duo Chan and Peter Huybers

Abstract

Most historical sea surface temperature (SST) estimates indicate warmer World War II SSTs than expected from forcing and internal climate variability. If real, this World War II warm anomaly (WW2WA) has important implications for decadal variability, but the WW2WA may also arise from incomplete corrections of biases associated with bucket and engine room intake (ERI) measurements. To better assess the origins of the WW2WA, we develop five different historical SST estimates (reconstructions R1–R5). Using uncorrected SST measurements from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) version 3.0 (R1) gives a WW2WA of 0.41°C. In contrast, using only buckets (R2) or ERI observations (R3) gives WW2WAs of 0.18° and 0.08°C, respectively, implying that uncorrected biases are the primary source of the WW2WA. We then use an extended linear-mixed-effect method to quantify systematic differences between subsets of SSTs and develop groupwise SST adjustments based on differences between pairs of nearby SST measurements. Using all measurements after applying groupwise adjustments (R4) gives a WW2WA of 0.13°C [95% confidence interval (c.i.): 0.01°–0.26°C] and indicates that U.S. and U.K. naval observations are the primary cause of the WW2WA. Finally, nighttime bucket SSTs are found to be warmer than their daytime counterparts during WW2, prompting a daytime-only reconstruction using groupwise adjustments (R5) that has a WW2WA of 0.09°C (95% c.i.: −0.01° to 0.18°C). R5 is consistent with the range of internal variability found in either the CMIP5 (95% c.i.: −0.10° to 0.10°C) or CMIP6 ensembles (95% c.i.: −0.11° to 0.10°C). These results support the hypothesis that the WW2WA is an artifact of observational biases, although further data and metadata analyses will be important for confirmation.

Open access
Zhaolu Hou, Jianping Li, and Bin Zuo

Abstract

Numerical seasonal forecasts in Earth science always contain forecast errors that cannot be eliminated by improving the ability of the numerical model. Therefore, correction of model forecast results is required. Analog correction is an effective way to reduce model forecast errors, but the key question is how to locate analogs. In this paper, we updated the local dynamical analog (LDA) algorithm to find analogs and depicted the process of model error correction as the LDA correction scheme. The LDA correction scheme was first applied to correct the operational seasonal forecasts of sea surface temperature (SST) over the period 1982–2018 from the state-of-the-art coupled climate model named NCEP Climate Forecast System, version 2. The results demonstrated that the LDA correction scheme improves forecast skill in many regions as measured by the correlation coefficient and root-mean-square error, especially over the extratropical eastern Pacific and tropical Pacific, where the model has high simulation ability. El Niño–Southern Oscillation (ENSO) as the focused physics process is also improved. The seasonal predictability barrier of ENSO is in remission, and the forecast skill of central Pacific ENSO also increases due to the LDA correction method. The intensity of the ENSO mature phases is improved. Meanwhile, the ensemble forecast results are corrected, which proves the positive influence from this LDA correction scheme on the probability forecast of cold and warm events. Overall, the LDA correction scheme, combining statistical and model dynamical information, is demonstrated to be readily integrable with other advanced operational models and has the capability to improve forecast results.

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Stephen Jewson, Sebastian Scher, and Gabriele Messori

Abstract

Users of meteorological forecasts are often faced with the question of whether to make a decision now, on the basis of the current forecast, or to wait for the next and, it is hoped, more accurate forecast before making the decision. Following previous authors, we analyze this question as an extension of the well-known cost–loss model. Within this extended cost–loss model, the question of whether to decide now or to wait depends on two specific aspects of the forecast, both of which involve probabilities of probabilities. For the special case of weather and climate forecasts in the form of normal distributions, we derive a simple simulation algorithm, and equivalent analytical expressions, for calculating these two probabilities. We apply the algorithm to forecasts of temperature and find that the algorithm leads to better decisions in most cases relative to three simpler alternative decision-making schemes, in both a simulated context and when we use reforecasts, surface observations, and rigorous out-of-sample validation of the decisions. To the best of our knowledge, this is the first time that a dynamic multistage decision algorithm has been demonstrated to work using real weather observations. Our results have implications for the additional kinds of information that forecasters of weather and climate could produce to facilitate good decision-making on the basis of their forecasts.

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Weixin Xu, Steven A. Rutledge, and Kyle Chudler

Abstract

Using 17-yr spaceborne precipitation radar measurements, this study investigates how diurnal cycles of rainfall and convective characteristics over the South China Sea region are modulated by the boreal summer intraseasonal oscillation (BSISO). Generally, diurnal cycles change significantly between suppressed and active BSISO periods. Over the Philippines and Indochina, where the low-level monsoon flows impinge on coast lines, diurnal cycles of rainfall and many convective properties are enhanced during suppressed periods. During active periods, diurnal variation of convection is still significant over land but diminishes over water. Also, afternoon peaks of rainfall and MCS populations over land are obviously extended in active periods, mainly through the enhancement of stratiform precipitation. Over Borneo, where the prevailing low-level winds are parallel to coasts, diurnal cycles (both onshore and offshore) are actually stronger during active periods. Radar profiles also demonstrate a pronounced nocturnal offshore propagation of deep convection over western Borneo in active periods. During suppressed periods, coastal afternoon convection over Borneo is reduced, and peak convection occurs over the mountains until the convective suppression is overcome in the late afternoon or evening. A major portion (>70%) of the total precipitation over the Philippines and Indochina during suppressed periods falls from afternoon isolated to medium-sized systems (<10 000 km2), but more than 70% of the active BSISO rainfall is contributed by nocturnal (after 1800 LT) broad precipitation systems (>10 000 km2). However, offshore total precipitation is dominated by large precipitation systems (>10 000 km2) regardless of BSISO phases and regions.

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