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Martin Rempel, Peter Schaumann, Reinhold Hess, Volker Schmidt, and Ulrich Blahak

Abstract

A wealth of forecasting models is available for operational weather forecasting. Their strengths often depend on the lead time considered, which generates the need for a seamless combination of different forecast methods. The combined and continuous products are made in order to retain or even enhance the forecast quality of the individual forecasts and to extend the lead time to potentially hazardous weather events. In this study, we further improve an artificial neural network–based combination model that was recently proposed in a previous paper. This model combines two initial precipitation ensemble forecasts and produces exceedance probabilities for a set of thresholds for hourly precipitation amounts. Both initial forecasts perform differently well for different lead times, whereas the combined forecast is calibrated and outperforms both initial forecasts with respect to various validation scores and for all considered lead times (from +1 to +6 h). Moreover, the robustness of the combination model is tested by applying it to a new dataset and by evaluating the spatial and temporal consistency of its forecasts. The changes proposed further improve the forecast quality and make it more useful for practical applications. Temporal consistency of the combined product is evaluated using a flip-flop index. It is shown that the combination provides a higher persistence with decreasing lead times compared to both input systems.

Free access
Yumeng Liu, Xianhong Meng, Lin Zhao, Zhaoguo Li, Hao Chen, Lunyu Shang, Shaoying Wang, Lele Shu, and Guangwei Li

Abstract

Under the intensification of global warming, the characteristics of the Three Rivers source region (TRSR; i.e., headwaters of the Yellow River, the Yangtze River, and the Lancang River) in China were diagnosed in the summer season from 1979 to 2015 using observations and reanalysis data. The diagnoses indicate that summer precipitation decreased from 1979 to 2002 [by 9.01 mm day−1 (10 yr)−1; p < 0.05 by Student’s t test] and increased significantly after 2002 [by 5.52 mm day−1 (10 yr)−1]. This abrupt change year (2002) was further confirmed by the cumulative anomaly method, the moving t-test method, and the Yamamoto method. By compositing the thermodynamics before and after the abrupt change year (2002), the results reveal that increased water vapor and more substantial lower-level convergence were present over the TRSR during 2003–15. This marked interdecadal variability in the TRSR summer precipitation responded to the interdecadal position and intensity of the large-scale forcing East Asian westerly jet (EAWJ), which is significantly modulated by the low-frequency variability associated with Southern Oscillation index. The connection between the interannual TRSR precipitation and the location and intensity of EAWJ was also explored. The position index of the EAWJ is negatively (with correlation coefficient R of −0.446; p < 0.05 by Student’s t test) correlated with the precipitation over the TRSR, implying that southward and northward years of EAWJ are respectively associated with intensifying and weakening the TRSR summer precipitation, whereas the intensity of EAWJ is insignificantly correlated with the TRSR summer precipitation.

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Xueheng Shi, Claudie Beaulieu, Rebecca Killick, and Robert Lund

Abstract

This paper presents a statistical analysis of structural changes in the Central England temperature series, one of the longest surface temperature records available. A changepoint analysis is performed to detect abrupt changes, which can be regarded as a preliminary step before further analysis is conducted to identify the causes of the changes (e.g., artificial, human-induced, or natural variability). Regression models with structural breaks, including mean and trend shifts, are fitted to the series and compared via two commonly used multiple changepoint penalized likelihood criteria that balance model fit quality (as measured by likelihood) against parsimony considerations. Our changepoint model fits, with independent and short-memory errors, are also compared with a different class of models termed long-memory models that have been previously used by other authors to describe persistence features in temperature series. In the end, the optimal model is judged to be one containing a changepoint in the late 1980s, with a transition to an intensified warming regime. This timing and warming conclusion is consistent across changepoint models compared in this analysis. The variability of the series is not found to be significantly changing, and shift features are judged to be more plausible than either short- or long-memory autocorrelations. The final proposed model is one including trend shifts (both intercept and slope parameters) with independent errors. The analysis serves as a walk-through tutorial of different changepoint techniques, illustrating what can be statistically inferred.

Open access
Jiuchang Wei, Qianwen Shao, Yang Liu, and Dora Marinova

Abstract

The link between climate change and human conflict has received substantial attention in academic research using different measures of “conflict”; however, it is yet to interpret interpersonal violence in terms of homicide. This study takes a global perspective to investigate how climate change, typically represented by temperature and precipitation, directly and indirectly affects national homicide rates across countries. From longitudinal archival data from 171 countries from 2000 to 2018, we detect a direct and positive relationship between higher temperatures and homicide, whereas an indirect pathway between wetter climate and homicide through the occurrence of more natural hazards has also been shown in our empirical results. The relationship between climate change and homicide can be moderated by the level of information and communication technologies (ICT). We conclude that the development of ICT contributes to building the countries’ resilience to climate change with better information and communication technologies to help alleviate the negative impacts of climate change on homicide.

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L. van Schalkwyk, R. C. Blamey, L. L. Dyson, and C. J. C. Reason

Abstract

A climatology of synoptic drylines on the subtropical southern African interior plateau (SAP) is developed using ERA5 reanalysis specific humidity and surface temperature gradients and an objective detection algorithm. Drylines are found to occur regularly during spring and summer (September–March), and almost daily during December of that period, but rarely in winter. A westward shift in peak dryline frequency takes place through the summer. Drylines peak first over the eastern parts of the SAP during November with a mean of 10 drylines and then over the central (mean of 12) and western SAP (mean of 20) in December. During midsummer, drylines over the eastern SAP are negatively correlated with drylines in the west. Between 1980 and 2020, a significant correlation exists between ENSO and dryline days over the eastern (r = 0.44; p value = 0.004) and central (r = 0.41; p value = 0.008) SAP with fewer drylines (up to 10) occurring during years with increased surface moisture and more drylines (up to 45) occurring during years with decreased surface moisture. Drylines forming over the eastern parts of the SAP were more likely to move westward than drylines over the central and western parts. Onset times across the SAP show that drylines have a tendency to form during either the late morning to early afternoon (1100 and 1400 LST) or during the early evening hours (1700 and 2000 LST), suggesting that the surface heat trough (Kalahari heat low) and westward moisture transport mechanisms, such as the Limpopo low-level jet and ridging highs, are responsible for the formation of most drylines across the SAP.

Significance Statement

“Drylines” are used to describe boundaries separating regions of very dry air from those with much higher moisture content. The importance of these drylines is that they tend to act as a trigger for thunderstorms, which can produce severe weather. In this study, we build a long-term climatological description of drylines in subtropical southern Africa. We find that drylines are most frequent over eastern South Africa during the early summer, a time when storms with large hail and damaging winds are most likely to occur. Drylines are sensitive to moisture circulation patterns and respond differently during El Niño and La Niña years, with generally more drylines during El Niño over eastern South Africa and fewer during La Niña.

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Seung-Hee Ham, Seiji Kato, Fred G. Rose, Sunny Sun-Mack, Yan Chen, Walter F. Miller, and Ryan C. Scott

Abstract

Cloud vertical profile measurements from the CALIPSO and CloudSat active sensors are used to improve top-of-atmosphere (TOA) shortwave (SW) broadband (BB) irradiance computations. The active sensor measurements, which occasionally miss parts of the cloud columns because of the full attenuation of sensor signals, surface clutter, or insensitivity to a certain range of cloud particle sizes, are adjusted using column-integrated cloud optical depth derived from the passive MODIS sensor. Specifically, we consider two steps in generating cloud profiles from multiple sensors for irradiance computations. First, cloud extinction coefficient and cloud effective radius (CER) profiles are merged using available active and passive measurements. Second, the merged cloud extinction profiles are constrained by the MODIS visible scaled cloud optical depth, defined as a visible cloud optical depth multiplied by (1 − asymmetry parameter), to compensate for missing cloud parts by active sensors. It is shown that the multisensor-combined cloud profiles significantly reduce positive TOA SW BB biases, relative to those with MODIS-derived cloud properties only. The improvement is more pronounced for optically thick clouds, where MODIS ice CER is largely underestimated. Within the SW BB (0.18–4 μm), the 1.04–1.90-μm spectral region is mainly affected by the CER, where both the cloud absorption and solar incoming irradiance are considerable.

Significance Statement

The purpose of this study is to improve shortwave irradiance computations at the top of the atmosphere by using combined cloud properties from active and passive sensor measurements. Relative to the simulation results with passive sensor cloud measurements only, the combined cloud profiles provide more accurate shortwave simulation results. This is achieved by more realistic profiles of cloud extinction coefficient and cloud particle effective radius. The benefit is pronounced for optically thick clouds composed of large ice particles.

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Peihao Zhou and Xiuzhen Li

Abstract

The meridional displacement of the western North Pacific subtropical high (WNPSH) on an intraseasonal time scale is investigated, with emphasis on differences between early (May–June) and late (July–August) summer. The intraseasonal variation (ISV) of the meridional displacement of the WNPSH is dominated by the 10–30-day period, and the variation amplitude is larger in late summer. The ISV of the WNPSH is attributed mainly to the evolution of an anomalous cyclone/anticyclone north of the WNPSH in early summer, whereas it is due to a south-to-north dipole of an anomalous anticyclone and cyclone over East Asia in late summer. Moreover, the WNPSH tends to shift westward when it moves northward, and vice versa, especially in early summer. Both tropical convection and mid- to high-latitude teleconnection across Eurasia are responsible for the ISV of the meridional displacement of the WNPSH in early and late summer. The role of mid- to high-latitude teleconnection is more important in early summer, whereas tropical convection over the South China Sea is more crucial in late summer, through triggering a Pacific–Japan (PJ) pattern. In early summer, as the WNPSH shifts northward, rainfall increases over the Yangtze River valley and decreases over Southeast China, and vice versa. In late summer, deficient rainfall over North China persists when the WNPSH is at its southernmost location and during its northward shift, and vice versa. The characteristics, underlying processes, and impacts of the 10–30-day meridional displacement of the WNPSH are significantly different in early and late summer.

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Kexin Song, Jiuwei Zhao, Ruifen Zhan, Li Tao, and Lin Chen

Abstract

Confidence and uncertainty issues of simulations were seldom evaluated in previous studies although the climate models are widely used. This study evaluates the performance of the CMIP6-HighResMIP simulations in presenting long-term variability of tropical cyclone (TC) genesis frequency (TCGF) and track density (TCTD) and quantifies the relative contributions of internal and external forcing to TC activities during the 1950–2014. There is overall poor model performance in simulating long-term changes in TC activities over the Northern Hemisphere, including interdecadal variabilities and long-term linear trends. The simulated long-term changes in TCGF and TCTD over the eastern North Pacific (ENP) in six high-resolution models show opposite characteristics to the observations. Moreover, most models cannot capture the variabilities of TCGF and TCTD over the western part of the western North Pacific (WNP) and northern part of the North Atlantic (NA). However, these models show a high degree of confidence in reproducing the interdecadal variabilities and linear trends of TCGF and TCTD over the eastern part of the WNP and the tropical NA. Quantitative evaluations further show that there are the opposite relative contributions of long-term climate variabilities to TCGF and TCTD changes over the ENP between the observations and the multimodel ensemble mean, followed by large model biases over the western WNP and the northern NA, but relatively consistent contributions over the southern NA and the Caribbean. These results help us cope with contrasting and consistent future TC changes among the model projections.

Significance Statement

While climate models have been widely used to project future changes in tropical cyclone (TC) activity, few studies have examined to what extent we can trust these model projections. We used the CMIP6-HighResMIP simulations to quantify the model biases in presenting TC activity, and evaluate the relative contributions of internal and external forcing to TC activities. In general, the HighResMIP has large discrepancies in representing longer-term climate variability of TC activity. However, the models can capture well TC activity over the eastern part of the western North Pacific and tropical Atlantic, which is attributed to good performance of models in reproducing the relationship between long-term climate variabilities beyond interannual scale and TC activity. These results highlight confidence and uncertainty in future TC changes among the model projections.

Open access
Stephen Jewson

Abstract

A 2020 metastudy by Knutson et al. gave distributions for possible changes in the frequency and intensity of tropical cyclones under climate change. The results form a great resource for those who model the impacts of tropical cyclones. However, a number of steps of processing may be required to use the results in practice. These include interpolation in time, distribution fitting, and reverse engineering of correlations. In this paper we study another processing step that may be required, which is adjusting the frequency change results so that they apply to landfalling frequencies. An adjustment is required because the metastudy results give frequency adjustments as a function of storm lifetime maximum intensity rather than landfall intensity. Increases in the frequency of category-4 and category-5 storms, by lifetime maximum intensity, then contribute to increases in the frequencies of storms of all intensities at landfall. We consider North Atlantic Ocean storms and use historical storm information to quantify this effect as a function of landfall intensity and region. Whereas the original metastudy results suggest that the mean frequency of category-3 storms will decrease, our analysis suggests that the mean frequency of landfalling category-3 storms will increase. Our results are highly uncertain, particularly because we assume that tracks and genesis locations of storms will not change, even though some recent climate model results suggest otherwise. However, making the adjustments we describe is likely to be a better way to model future landfall risk than applying the original metastudy frequency changes directly at landfall.

Significance Statement

A recent metastudy gave distributions for possible changes in the frequency and intensity of tropical cyclones under climate change. For the North Atlantic Ocean, we show how to convert these results to changes at landfall. This conversion increases the changes in the frequencies of storms in intensity categories 0–3, and, in particular, the mean frequency change of storms in category 3 flips from decreasing to increasing in most regions.

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Daniel J. Halperin, Thomas A. Guinn, Sarah E. Strazzo, and Robert L. Thomas

Abstract

Density altitude (DA) is an aviation parameter that helps determine specific aircraft performance characteristics for the expected atmospheric conditions. However, there are currently no detailed graphical tools for general aviation (GA) pilot education demonstrating the spatial and temporal variation of DA to help improve situational awareness. In this study, the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate (ERA5) dataset is used to construct a 30-yr monthly climatology of DA for the conterminous United States. Several DA characteristics are also investigated, including the effect of humidity on DA, the determination of reasonable worst-case conditions, and the applicability of two DA rules of thumb (ROTs). Maximum values of DA (worst aircraft performance) occur during July, reaching 3600 m over areas with high surface elevations. Humidity, while tertiary to the effects of temperature and pressure, causes the DA to increase from their dry values by more than 140 m as far north as the U.S.-Canada border. The dry DA ROT performs well for all conditions outside of strong tropical cyclones, where GA flights would not be expected. The ROT to correct for the effects of humidity performs well except in high elevations or when the dewpoint temperatures fall outside the applicable range of ≥5°C. When applied outside this range, in some situations, DA errors can be greater than if no humidity correction were applied. Therefore, a new ROT to correct for humidity is introduced here that extends the applicable dewpoint temperature range to ≥−28°C and reduces errors in estimated DA.

Significance Statement

The impacts of density altitude on aircraft performance have led to numerous general aviation (GA) accidents. This study helps GA pilots better understand the spatial and temporal variability in density altitude, thereby increasing their situational awareness during flight planning. This study also evaluates commonly used approximations to estimate density altitude, so pilots can understand the situations where these approximations are (in)applicable. Results suggest the need for a humidity correction approximation when dewpoint temperatures are <5°C, which is introduced in this study.

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