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Each physical process in a numerical weather prediction (NWP) system may have many different parameterization schemes. Early studies have shown that the performance of different physical parameterization schemes varies with the weather situation to be simulated. Thus, it is necessary to select a suitable combination of physical parameterization schemes according to the variation of weather systems. However, it is rather difficult to identify an optimal combination among millions of possible parameterization scheme combinations. This study applied a simple genetic algorithm (SGA) to optimizing the combination of parameterization schemes in NWP models for typhoon forecasting. The feasibility of SGA was verified with the simulation of Typhoon Mujigae (2015) by using the Weather Research and Forecasting (WRF) model and Typhoon Higos (2020) by using the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system. The results show that SGA can efficiently obtain the optimal combination of schemes. For Typhoon Mujigae (2015), the optimal combination can be found from the 1,304,576 possible combinations by running only 488 trials. Similar results can be obtained for Typhoon Higos (2020). Compared to the default combination proposed by the COAWST model system, the optimal combination scheme significantly improves the simulation of typhoon track and intensity. This study provides a feasible way to search for the optimal combinations of physical parameterization schemes in WRF and COAWST for more accurate typhoon simulation. This can help provide references for future development of NWP models, and for analyzing the coordination and adaptability of different physical process parameterization schemes under specific weather backgrounds. [ABSTRACT FROM AUTHOR]

Although the North Atlantic (NA) hurricane season has been reported to start increasingly early, historical long-term changes in NA spring tropical cyclone (TC) activity have not been examined in previous studies. We find that spring TCs have become more frequent and intense, and they have more closely approached the US coastline over the past four decades, thus increasing the probability of landfall. A long-term increase in the NA sea surface temperature (SST) and northward incursion of warm water may be responsible for the increasing number, intensity, and northward shift of spring TCs. In addition, the interdecadal winter NA SST tripole mode may induce a North Atlantic Oscillation (NAO)-like atmospheric response in the following spring, which controls spring TC tracks via modulating the strength and position of the NA subtropical high (or the Bermuda high). The superposition of the interdecadal positive winter SST tripole on the NA warming trend has contributed to the anomalous enhancement and northward shift of spring TC activity, increasing the spring TC risks in the US in the past six years. [ABSTRACT FROM AUTHOR]

Landfalling typhoons can cause disasters over large regions. The government and emergency responders need to take measures to mitigate disasters according to the forecast of landfall position, while slight timing error can be ignored. The reliability of operational model forecasts of typhoon landfall position needs to be evaluated beforehand, according to the forecasts and observation of historical cases. In the evaluation of landfalling typhoon track, the traditional method based on point-to-point matching methods could be influenced by the predicted typhoon translation speed. Consequently, the traditional track evaluation method may result in a large track error even if the predicted landfall position is close to observation. The purpose of this paper is to address the above issue using a simple evaluation method of landfalling typhoon track forecast based on the time neighborhood approach. In this new method, the timing error was lessened to highlight the importance of the position error during the landfall of typhoon. The properties of the time neighborhood method are compared with the traditional method based on numerical forecast results of 12 landfalling typhoon cases. Results demonstrated that the new method is not sensitive to the sampling frequency, and that the difference between the time neighborhood and traditional method will be more obvious when the moving speed of typhoon is moderate (between 15–30 km h−1). The time neighborhood concept can be easily extended to a broader context when one attempts to examine the position error more than the timing error. [ABSTRACT FROM AUTHOR]

The Indo-Pacific warm pool (IPWP), which affects the global climate system through supporting tropical convection, has been reported to expand significantly under greenhouse warming. Although early research revealed that the sea surface temperature (SST) threshold for deep convection (σconv) increases with global warming, many latest relevant works were still conducted based on the traditional IPWP definition (e.g., static SST = 28 °C threshold, and is referred to as the oceanic warm pool, OWP28). Here, we claim that the OWP28 expansion differs from the deep convection favoring pool (DCFP) area change and may not reflect the direct impacts of Indo-Pacific warming on the climate system. Results show that, because of the long-term increase in σconv, the DCFP expands at a rate 2.6 times slower than the OWP28 from 1979 to 2020. The difference reaches 12–27 times from 2015–2100 under different emission scenarios, based on CMIP6 model simulations. While the OWP28 expands to the eastern Pacific, the DCFP will remain within the Indian Ocean and western Pacific Ocean regardless of emission levels. This study emphasizes the necessity of considering the response of the relationship between deep convection and SST to climate change when studying the long-term variability of the IPWP. [ABSTRACT FROM AUTHOR]

Model simulations suggest that Madden–Julian oscillation (MJO) activity changes under the anthropogenic climate change background. However, satellite observations, which provide information on MJO convection activity, are not available before the 1970s, hindering research on the long-term historical variability of MJO. This study aims at extending the data length of MJO indices that include both MJO circulation and convection features, such as the widely used Real-Multivariate MJO (RMM) Index, to the pre-satellite era. This paper introduces a new MJO Index construction method, in which the outgoing longwave radiation (OLR) input is derived from upper-level geopotential, and names it as the Geopotential-Based Multivariate MJO (GMM) Index. The GMM Index is derived from 1902 to 2008 based on the 20th century reanlaysis product, by assuming that the relationship between OLR and geopotential does not change over time, and is compared with the filtered version of the RMM (FMM) Index during 1981–2008 and historical observed precipitation records in the 20th century. The GMM Index is shown to (1) have the same climatological properties as the FMM Index, (2) be statistically highly correlated to the FMM Index, and (3) be able to indicate MJO activities and MJO's convection features in the pre-satellite era. The overall bivariate correlation between the FMM and GMM indices based on ERA-20C is 0.964. Evaluation results confirm the validity of the proposed MJO Index construction method, which could capture MJO convection activity in the pre-satellite era and can be applied to all MJO indices that require OLR inputs. This study provides an alternative way that overcomes the difficulty of historical MJO studies and will be beneficial to our understanding of the long-term change of MJO. [ABSTRACT FROM AUTHOR]

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Low visibility episodes (visibility < 1000 m) were studied by applying the anomaly-based weather analysis method. A regional episode of low visibility associated with a coastal fog that occurred from 27 to 28 January 2016 over Ningbo-Zhoushan Port, Zhejiang Province, East China, was first examined. Some basic features from the anomalous weather analysis for this case were identified: (1) the process of low visibility mainly caused by coastal fog was a direct response to anomalous temperature inversion in the lower troposphere, with a warm center around the 925 hPa level, which was formed by a positive geopotential height (GPH) anomaly in the upper troposphere and a negative GPH anomaly near the surface; (2) the positive humidity anomaly was conducive to the formation of coastal fog and rain; (3) regional coastal fog formed at the moment when the southwesterly wind anomalies transferred to northeasterly wind anomalies. Other cases confirmed that the low visibility associated with coastal fog depends upon low-level inversion, a positive humidity anomaly, and a change of wind anomalies from southwesterly to northeasterly, rain and stratus cloud amount. The correlation coefficients of six-hourly inversion, 850–925-hPa-averaged temperature, GPH and humidity anomalies against visibility are −0.31, 0.40 and −0.48, respectively, reaching the 99% confidence level in the first half-years of 2015 and 2016. By applying the anomaly-based weather analysis method to medium-range model output products, such as ensemble prediction systems, the anomalous temperature-pressure pattern and humidity—wind pattern can be used to predict the process of low visibility associated with coastal fog at several days in advance. [ABSTRACT FROM AUTHOR]

In this article, the synoptic-scale spatial structures for raising tornadic and hail storms are compared by analyzing the total and anomalous variable fields from the troposphere to the stratosphere. 15 cases of tornado outbreaks and 20 cases of hail storms that occurred in the central United States during 1980–2011 were studied. The anomalous temperature–height field shows that a tornadic or hail storm usually occurs at the boundary of anomalous warm and cold air masses horizontally in the troposphere. In one side, an anomalous warm air mass in the mid-low troposphere and an anomalous cold air mass in the stratosphere are vertically separated by a positive center of height anomalies at the upper troposphere. In another side, an opposite vertical pattern shows that an anomalous cold air mass in the mid-low troposphere and an anomalous warm air mass in the stratosphere are separated by a negative center of height anomalies at the upper troposphere. Therefore, two pairs of adjacent anomalous warm/cold centers and one pair of anomalous high/low centers combining together form a major tornadic or hail storm paradigm, which can be physically considered as the storage of anomalous potential energy (APE) to generate severe weather. To quantitatively measure the APE, we define an index of anomalous convective instability (ACI) which is a difference of integrating temperature anomalies based on two vertically opposite anomalous air masses. The APE transformation to anomalous kinetic energy, which reduces horizontal and vertical gradients of temperature anomalies, produces anomalous rising and sinking flows in the lower-layer anomalous warm and cold air mass sides, respectively. The intensity of ACI index for tornadic storm cases is 1.5 times larger than that of hail storm cases in average. Thus, this expression of anomalous variables is better than total variables used in the traditional synoptic chart and the ACI index is better than other indices to detect potential tornadic and hail storms in order to understand the environmental conditions affecting severe weather in analytical and model output datasets. [ABSTRACT FROM AUTHOR]

This paper examines the three-dimensional geopotential height structure of the Madden-Julian oscillation (MJO) and proposes that the MJO convection signals can be well reflected by upper-tropospheric zonal anomalous height gradient (ZAHG, $$\nabla_{x} z'$$ ). A case study in 2011 and composite analyses have been done by applying a wavenumber-frequency filtering method on daily variable anomalies derived from different reanalysis datasets. Results show that the upper-level eastward-moving intraseasonal geopotential height anomaly does not exactly display a Rossby-Kelvin wave structure of the Gill model. Instead, it shows a height quadrupole pattern and is well associated with temperature and zonal wind anomalies. The notable tilted upper-tropospheric temperature structure can be derived from the height anomalies by the hydrostatic balance relationship. The first baroclinic mode vertical structure of zonal wind anomalies can be approximated from the height anomalies by the geostrophic equation. A highlight of the paper is the proposal of tracing the MJO convection center by the upper-tropospheric ZAHG ( $$\nabla_{x} z'$$ ). Composite analyses of all MJO events during extended winter (NDJFM) from 1979 to 2013 suggest that positive upper-tropospheric ZAHG is exactly in phase with negative outgoing longwave radiation (OLR) anomalies in the eastern Indian Ocean and Maritime Continent during a MJO event. On the other hand, positive upper-tropospheric ZAHG leads (lags) negative OLR anomalies by 1 (2) days in the western Indian Ocean (western Pacific Ocean), where MJO events generally initiate (dissipate). ZAHG can also be applied to modeling data and observation data before the satellite era. This study provides a new diagnostic parameter option to monitor MJO events, and an alternative for studying MJOs before the satellite era and model evaluation. [ABSTRACT FROM AUTHOR]

The Arctic cell as a reversed and closed loop next to the Polar cell has been recently revealed in the Northern Hemisphere (NH). In this paper, we study the interannual variability of the Arctic and Polar cell strengths during 1979-2012, and their influence on surface air temperature (SAT), precipitation, and sea-ice concentration (SIC) at mid- and high-latitudes of the NH. We show that there is a significant negative correlation between the Arctic and Polar cell strengths. Both the Arctic and Polar cell strengths can well indicate the recurring climatic anomalies of SAT, precipitation, and SIC in their extreme winters. The surface large-scale cold-warm and dry-wet anomalous patterns in these extreme winters are directly linked with the vertical structure of height and temperature anomalies in the troposphere. Results suggest that the past climatic anomalies are better indicated by the strength anomalies of the Polar and Arctic cells than the traditional indices of mid-high latitude pattern such as the Arctic Oscillation and North Atlantic Oscillation. This study illustrates a three-dimensional picture of atmospheric variable anomalies in the troposphere that result in surface climatic anomalies. [ABSTRACT FROM AUTHOR]

The global monsoon domain has been recently determined utilizing two criteria: difference of local maximum and minimum pentad-mean precipitation rates exceeding 4 mm day, and wind reversal of low-level cross-equatorial flow. In this paper, 22 major dry-wet alteration regions under six categories were first derived through the k-means clustering method from the climatological evolution of global precipitation. Considering the seasonal influences of the low-level cross-equatorial flow in these major dry-wet alternation regions, the global monsoon was objectively divided into 16 major regions under five climatological precipitation categories. Nine monsoon regions are distributed between Asia and Australia while four regions are from Africa to the Southwest Indian Ocean and three regions in Americas. Precipitation trends during rainy seasons of 1981-2010 were examined in the 16 monsoon regions. Four regions with decreasing trends of precipitation are located in Africa and the Southwest Indian Ocean while three regions with increasing trends are situated in Americas. Six regions of increasing precipitation trends are concentrated in Asia and the biggest increasing trend is found in south China. [ABSTRACT FROM AUTHOR]