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Chao Zhang, XiaoJing Jia, and Zhiping Wen

Abstract

This study investigated the increased impact of the spring (March–May) snow-cover extent (SCE) over the western Tibetan Plateau (TP) (SSTP) to the mei-yu rainfall [June–July (JJ)] over the Yangtze River valley (YRV) (MRYRV) after the 1990s. The correlation between the MRYRV and SSTP is significantly increased from the period of 1970–92 (P1) to 1993–2015 (P2). In P1, the MRYRV-related SSTP anomalies are located over the southwest TP, which causes a perturbation near the subtropical westerly jet (SWJ) core and favors an eastward propagation in the form of a wave train. The wave train results in a southward shift of the SWJ over the ocean south of Japan in JJ and exerts a limited effect on the MRYRV. Differently, in P2, the MRYRV-related anomalous SSTP causes an anomalous cooling temperature and upper-level cyclonic system centered over the northwestern TP. The cyclonic system develops and extends eastward to the downstream region with time and reaches coastal East Asia in JJ. The anomalous westerly winds along its south flank cause an enhanced SWJ, which is accompanied by an anomalous lower-level air convergence and ascent motion near the YRV region, favoring enhanced MRYRV. In addition, the forecast experiments performed with empirical regression models illustrate that the prediction skill of the MRYRV variation is clearly increased in P2 with the additional forecast factor of the SSTP.

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Yuqing Wang, Yuanlong Li, Jing Xu, Zhe-Min Tan, and Yanluan Lin

Abstract

In this study, a simple energetically based dynamical system model of tropical cyclone (TC) intensification is modified to account for the observed dependence of the intensification rate (IR) on the storm intensity. According to the modified dynamical system model, the TC IR is controlled by the intensification potential (IP) and the weakening rate due to surface friction beneath the eyewall. The IP is determined primarily by the rate of change in the potential energy available for a TC to develop, which is a function of the thermodynamic conditions of the atmosphere and the underlying ocean, and the dynamical efficiency of the TC system. The latter depends strongly on the degree of convective organization within the eyewall and the inner-core inertial stability of the storm. At a relatively low TC intensity, the IP of the intensifying storm is larger than the frictional weakening rate, leading to an increase in the TC IR with TC intensity in this stage. As the storm reaches an intermediate intensity of 30–40 m s−1, the difference between IP and frictional weakening rate reaches its maximum, concurrent with the maximum IR. Later on, the IR decreases as the TC intensifies further because the frictional dissipation increases with TC intensity at a faster rate than the IP. Finally, the storm approaches its maximum potential intensity (MPI) and the IR becomes zero. The modified dynamical system model is validated with results from idealized simulations with an axisymmetric nonhydrostatic, cloud-resolving model.

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Hua He, Guorong Chai, Yana Su, Yongzhong Sha, Shengliang Zong, and Hairong Bao

Abstract

This study assessing the lag and interactive effects between the daily average temperature and relative humidity on respiratory disease (RD) morbidity in Lanzhou, China, using data from daily outpatient visits for RD between 2014 and 2017 and meteorological and pollutant data during the same period analyzed with Poisson generalized linear model and distributed lag nonlinear models; the effects are further explored by classifying the RD by gender, age, and disease type. The results showed that the effect of temperature and relative humidity on outpatient visits of different populations and types of RD is nonlinear, with a significant lag effect. Relative to 11°C, every 1°C decrease in temperature is associated with 10.98% [95% confidence interval (CI): 9.87%–12.11%] increase for total RD. Chronic obstructive pulmonary disease is affected only by low temperature, upper respiratory tract infection is affected by both low and high temperatures, and asthma is influenced by high temperature. When the relative humidity is less than 32%, every 1% decrease in relative humidity is associated with 6.00% (95% CI: 3.00%–9.11%) increase for total RD; relative humidity has different effects on the outpatient risk of different types of RD. Temperature and relative humidity have an obvious interactive effect on different types and populations of RD: when both temperature and humidity are at low levels, the number of outpatient visits for RD is higher. When the relative humidity is ≤50% and the temperature is ≤11°C, total RD outpatient visits increase by 4.502% for every 1°C drop in temperature; that is, a dry environment with low temperature has the most significant impact on RD.

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Yuntao Jian, Marco Y. T. Leung, Wen Zhou, Maoqiu Jian, Song Yang, and Xiaoxia Lin

Abstract

In this study, the interdecadal variability of the relationship between ENSO and winter synoptic temperature variability (STV) over the Asian–Pacific–American region is investigated based on observational data from 1951 to 2018. An interdecadal shift in the ENSO–STV relationship occurred in the 1980s over Eastern China, changing from significant in period 1 (P1; 1951–87) to insignificant in period 2 (P2; 1988–2018). But the ENSO–STV relationship is significantly stable over North America for the whole period. In addition, a possible reason for this interdecadal shift in the ENSO–STV relationship over Eastern China is also investigated. During P1, the ENSO pattern is significantly correlated to the temperature gradient over Northeast Asia, which is the key region influencing the intensification of extratropical eddies. The intensification of extratropical eddies over Northeast Asia is directly associated with the magnitude of STV over Eastern China. But in P2, the ENSO pattern is not related to the temperature over Northeast Asia. Therefore, the change in the ENSO pattern from P1 to P2 contributes to the interdecadal shift in the ENSO–STV relationship in the 1980s over Eastern China by influencing the temperature gradient over Northeast Asia, while ENSO can influence the temperature gradient over North America for the whole period. Furthermore, the possible role of the ENSO patterns in P1 and P2 is also examined by using an atmospheric general circulation model, highlighting that the pattern of SST variation is a determining factor in regulating STV in different regions.

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Christopher Bladwell, Ryan M. Holmes, and Jan D. Zika

Abstract

The global water cycle is dominated by an atmospheric branch that transfers freshwater away from subtropical regions and an oceanic branch that returns that freshwater from subpolar and tropical regions. Salt content is commonly used to understand the oceanic branch because surface freshwater fluxes leave an imprint on ocean salinity. However, freshwater fluxes do not actually change the amount of salt in the ocean and—in the mean—no salt is transported meridionally by ocean circulation. To study the processes that determine ocean salinity, we introduce a new variable “internal salt” along with its counterpart “internal fresh water.” Precise budgets for internal salt in salinity coordinates relate meridional and diahaline transport to surface freshwater forcing, ocean circulation, and mixing and reveal the pathway of freshwater in the ocean. We apply this framework to a 1° global ocean model. We find that for freshwater to be exported from the ocean’s tropical and subpolar regions to the subtropics, salt must be mixed across the salinity surfaces that bound those regions. In the tropics, this mixing is achieved by parameterized vertical mixing, along-isopycnal mixing, and numerical mixing associated with truncation errors in the model’s advection scheme, whereas along-isopycnal mixing dominates at high latitudes. We analyze the internal freshwater budgets of the Indo-Pacific and Atlantic Ocean basins and identify the transport pathways between them that redistribute freshwater added through precipitation, balancing asymmetries in freshwater forcing between the basins.

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Basanta Raj Adhikari

Abstract

Lightning is one of the most devastating hazards in Nepal because of a large amount of atmospheric water vapor coming from the Indian Ocean and a large orographic lifting of this moist air. In 2019, a total of 2884 people were affected, with loss of USD 110,982, and the fatality number was the highest (94) in reported lightning events since 1971. The long-term analysis of this hazard is very scanty in Nepal. Therefore, this study analyzes lightning fatality events, fatality rates, and economic loss from 1971 to 2019 collected from the DesInventar dataset and the Disaster Risk Reduction portal of the government of Nepal using Statistical Package for Social Sciences (SPSS) and geographic information system (ArcGIS) tools. The analysis shows that the overall countrywide lightning fatality rate of the entire period is 1.77 per million per year. District lightning fatality rates range from 0.10 to 4.83 per million people per year, and the Bhaktapur district has the highest fatality density (0.067). Furthermore, there were a total of 2501 lightning fatality events in which 1927 people lost their lives and 20 569 people were affected. The increase in lightning fatality events in recent years is due to internet penetration and other measures of information gathering that result in lightning fatality reports reaching agencies collecting information. The high and low concentrations of loss and damage are mainly due to geographic distribution, population density, and economic activities. This study recommends the establishment of lightning early warning systems in the Nepal Himalayas to save life and property.

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Ronald L. Holle, William A. Brooks, and Kenneth L. Cummins

Abstract

National park visitors travel primarily to view natural features while outdoors; however, visits often occur in warmer months when lightning is present. This study uses cloud-to-ground flashes from 1999 to 2018 and cloud-to-ground strokes from 2009 to 2018 from the National Lightning Detection Network to identify lightning at the 46 contiguous United States national parks larger than 100 km2. The largest density is 6.10 flashes per kilometer squared per year within Florida’s Everglades, and the smallest is near zero in Pinnacles National Park. The six most-visited parks are Great Smoky Mountains, Grand Canyon, Rocky Mountain, Zion, Yosemite, and Yellowstone. For each of these parks, lightning data are described by frequency and location as well as time of year and day. The four parks west of the Continental Divide have most lightning from 1 July to 15 September and from 1100 to 1900 LST. Each park has its own spatial lightning pattern that is dependent on local topography. Deaths and injuries from lightning within national parks have the same summer afternoon dominance shown by lightning data. Most casualties occur to people visiting from outside the parks’ states. The most common activities and locations are mountain climbing, hiking, and viewing canyons from overlooks. Lightning fatality risk, the product of areal visitor and CG flash densities, shows that many casualties are not in parks with high risk, while very small risk indicates parks where lightning awareness efforts can be minimized. As a result, safety advice should focus on specific locations such as canyon rims, mountains, and exposed high-altitude roads where lightning-vulnerable activities are engaged in by many visitors.

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Kevin M. Grise and Mitchell K. Kelleher

Abstract

An effective method to understand cloud processes and to assess the fidelity with which they are represented in climate models is the cloud controlling factor framework, in which cloud properties are linked with variations in large-scale dynamical and thermodynamical variables. This study examines how midlatitude cloud radiative effects (CRE) over oceans covary with four cloud controlling factors—midtropospheric vertical velocity, estimated inversion strength (EIS), near-surface temperature advection, and sea surface temperature (SST)—and assesses their representation in CMIP6 models with respect to observations and CMIP5 models. CMIP5 and CMIP6 models overestimate the sensitivity of midlatitude CRE to perturbations in vertical velocity and underestimate the sensitivity of midlatitude shortwave CRE to perturbations in EIS and temperature advection. The largest improvement in CMIP6 models is a reduced sensitivity of CRE to vertical velocity perturbations. As in CMIP5 models, many CMIP6 models simulate a shortwave cloud radiative warming effect associated with a poleward shift in the Southern Hemisphere (SH) midlatitude jet stream, an effect not present in observations. This bias arises because most models’ shortwave CRE are too sensitive to vertical velocity perturbations and not sensitive enough to EIS perturbations, and because most models overestimate the SST anomalies associated with SH jet shifts. The presence of this bias directly impacts the transient surface temperature response to increasing greenhouse gases over the Southern Ocean, but not the global-mean surface temperature. Instead, the models’ climate sensitivity is correlated with their shortwave CRE sensitivity to surface temperature advection perturbations near 40°S, with models with more realistic values of temperature advection sensitivity generally having higher climate sensitivity.

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William E. Chapman, Aneesh C. Subramanian, Shang-Ping Xie, Michael D. Sierks, F. Martin Ralph, and Youichi Kamae

Abstract

Using a high-resolution atmospheric general circulation model simulation of unprecedented ensemble size, we examine potential predictability of monthly anomalies under El Niño–Southern Oscillation (ENSO) forcing and background internal variability. This study reveals the pronounced month-to-month evolution of both the ENSO forcing signal and internal variability. Internal variance in upper-level geopotential height decreases (~10%) over the North Pacific during El Niño as the westerly jet extends eastward, allowing forced signals to account for a greater fraction of the total variability, and leading to increased potential predictability. We identify February and March of El Niño years as the most predictable months using a signal-to-noise analysis. In contrast, December, a month typically included in teleconnection studies, shows little to no potential predictability. We show that the seasonal evolution of SST forcing and variability leads to significant signal-to-noise relationships that can be directly linked to both upper-level and surface variable predictability for a given month. The stark changes in forced response, internal variability, and thus signal-to-noise across an ENSO season indicate that subseasonal fields should be used to diagnose potential predictability over North America associated with ENSO teleconnections. Using surface air temperature and precipitation as examples, this study provides motivation to pursue “windows of forecast opportunity” in which statistical skill can be developed, tested, and leveraged to determine times and regions in which this skill may be elevated.

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Deepashree Dutta, Steven C. Sherwood, Katrin J. Meissner, Alex Sen Gupta, Daniel J. Lunt, Gregory J. L. Tourte, Robert Colman, Sugata Narsey, David Fuchs, and Josephine R. Brown

Abstract

When simulating past warm climates, such as the early Cretaceous and Paleogene periods, general circulation models (GCMs) underestimate the magnitude of warming in the Arctic. Additionally, model intercomparisons show a large spread in the magnitude of Arctic warming for these warmer-than-modern climates. Several mechanisms have been proposed to explain these disagreements, including the unrealistic representation of polar clouds or underestimated poleward heat transport in the models. This study provides an intercomparison of Arctic cloud and atmospheric heat transport (AHT) responses to strong imposed polar-amplified surface ocean warming across four atmosphere-only GCMs. All models simulate an increase in high clouds throughout the year; the resulting reduction in longwave radiation loss to space acts to support the imposed Arctic warming. The response of low- and midlevel clouds varies considerably across the models, with models responding differently to surface warming and sea ice removal. The AHT is consistently weaker in the imposed warming experiments due to a large reduction in dry static energy transport that offsets a smaller increase in latent heat transport, thereby opposing the imposed surface warming. Our idealized polar amplification experiments require very large increases in implied ocean heat transport (OHT) to maintain steady state. Increased CO2 or tropical temperatures that likely characterized past warm climates reduce the need for such large OHT increases.

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