Reduction in precipitation seasonality in China from 1960 to 2018

Changes in precipitation seasonality or the distribution of precipitation have important impacts on hydrological extremes (e.g., floods or droughts). Precipitation extremes have been widely reported to increase with global warming; however, the variability and mechanism of precipitation seasonality have not been well quantified in China. Here, we explore the multiscale variability in precipitation seasonality from 1960 to 2018 in China. A seasonality index of precipitation is defined to quantify the precipitation seasonality with a lower value indicating a more even distribution throughout a year. The seasonality index increases from southeastern to northwestern China, with a decrease in the annual mean precipitation, a later timing of the wet season, and a shorter wet season duration. The seasonality index decreases from 1960 to 2018 in China, accompanied by the increasing duration of wet season, especially in northern climate-sensitive basins, such as the Northwest River, Hai River and Songliao River basins. Take the Northwest River basin for example, the observed significant decrease in the seasonality index (~0.02/decade) from 1960 to 2018 is consistent with a significant decrease in the ratio of annual maximum 10-day precipitation to annual precipitation, which is confirmed by their significant positive correlation (R=0.72, p=0). The El Niño–Southern Oscillation (ENSO) dominates interannual fluctuations and spatial patterns of precipitation seasonality in China. In EI Niño years, the precipitation seasonality index decreases across China except for the Yangtze River basin, with broad increases in annual precipitation.

Evaluation of Diverse-based Precipitation Data Over the Amazon Region

The skill of the diverse-based precipitation products is investigated in comparison with HYBAM rain-gauge observations. The performance of three remote sensing-based datasets (the Climate Hazards Group InfraRed Precipitation with Station, CHIRPS, the Multi-Source Weighted-Ensemble Precipitation, MSWEP, and the Tropical Rainfall Measuring Mission, TRMM) is evaluated considering different timescales for the Amazon Basin, an area with widely heterogeneous precipitation. The analysis considered seasonal, intraseasonal and diurnal timescales through the computation of the cluster analysis, the seasonality index, the Kling-Gupta Efficiency metric, spectral analysis and composing technique. CHIRPS has the lowest performance to represent the rainfall in the northwest portion of the basin, where it underestimated the mean precipitation compared to the other bases. In this region, the other remote sensing-based (TRMM and MSWEP databases) compared to HYBAM also showed considerable variability and misrepresentation of the intraseasonal rainfall. In general, all databases perform better in the north and eastern portions of the basin compared to HYBAM. The comparison of the diurnal rainfall cycle between remote sensing-based data and the field campaigns of TRMM-LBA and GoAmazon, and the Huayao station in the Andes was also evaluated. At the diurnal timescale, MSWEP predates the time of the rainfall peak, but represents the magnitude of the precipitation well compared with TRMM. This study is necessary to warn about the importance of a more complete and objective assessment of the data before considering it for applications in different precipitation studies, mainly in regions with high rainfall heterogeneity like the Amazon Basin.

Changing low flow seasonality in Central European headwaters

<p>In the environment of the changing climate in Central Europe, the seasonality and magnitude of low flow events and hydrological droughts are projected to change in the near future. Ongoing increases in the air temperature, rates of evaporation and decreasing snow cover will significantly affect the summer deficit volumes even in the rivers of humid montane and highland areas in mid-latitudes. However, what if the significant changes have already been happening during the last decades? Therefore, this research is focused on analysis of the variability and seasonality of low flow events and hydrological drought events in fifteen near-natural catchments along the Czech–German and Czech–Polish national borders. To quantify the low flow regime changes of the study regions in the last 52 years (1968–2019), we applied tools from the R package lfstat. The 30-year moving averages of seasonality ratio (SR) and the seasonality index (SI) were derived to address the degree of change in each catchment. Moreover, the 7-day and 30-day mean summer minimum discharges were computed, as well as the streamflow deficit volumes for every episode of hydrological drought. The results showed a continual increase in the proportion of summer low flow and drought events during the study period along with a significant shift in the average date of low flow occurrence towards the beginning of the year. The most marked shifts in low flow seasonality were found mainly in catchments with the average altitude 800–1000 m a. s. l. Conversely, the low flow regime in catchments above 1000 m a. s. l. and also in the catchments below 800 m a. s. l. remained nearly stable throughout the 1968–2019 period. Moreover, the analysis of 7- and 30-day mean summer minimum discharges indicated a much-diversified pattern in the behavior of long-term trends than it was expected.</p>

Pola Musiman Kunjungan Wisatawan Mancanegara Ke Bali

The seasonal pattern of tourist arrivals is an important element that must be observed in making policies in the field of tourism marketing. By using the method of calculation, the Seasonality Ratio, Gini Coefficients, and Seasonality Index, this study aims to identify seasonal patterns of foreign tourist arrivals to Bali during the past 5 years. This study shows that: First, foreign tourists’ arrivals to Bali showed insignificant levels of variation and an equation of seasonal variations patterns is found in 2015, 2016, and 2019. Second, foreign tourist arrivals to Bali had a distribution per month that is relatively evenly distributed, with low seasonal rates, or the difference between monthly arrivals has an insignificant difference in value. Third, peak season of foreign tourists’ arrivals to Bali was concentrated in July with a drastic increase from the previous month and accompanied by a slowing decline towards the off-peak season. So, it is necessary to do an appropriate marketing and resource allocation strategies to optimize each seasonal phase.

INTRA-ANNUAL DYNAMICS OF MORTALITY RATES IN CITIES OF THE SOUTHERN PART OF THE RUSSIAN FAR EAST

The analysis of the intra-annual dynamics of mortality rates features from all causes and from cardiorespiratory diseases, using the seasonality index, showed the maximum mortality rate in cities of the Far East south in winter, and the minimum-in summer. A detailed analysis of mortality caused by cardiorespiratory diseases in the older age cohort has revealed a higher risk of pathologies in winter periods, with a maximum in February. A relative indicator decline in November, apparently associated with the so-called «harvest effect», when excess mortality in one period (in October) is compensated by the indicator decrease in the subsequent time period. For the elderly population in Khabarovsk, the maximum death rate in January and its sharp rise in October repeats the picture of all-cause mortality with little gender difference. For men – residents of Vladivostok-the maximum development of cardiovascular disasters occurs in January, a slight increase in mortality is observed in May and October, and the minimum-in August and September, with an annual dynamics with an amplitude of 20%.

Changing Low Flow and Streamflow Drought Seasonality in Central European Headwaters

In the context of the ongoing climate warming in Europe, the seasonality and magnitudes of low flows and streamflow droughts are expected to change in the future. Increasing temperature and evaporation rates, stagnating precipitation amounts and decreasing snow cover will probably further intensify the summer streamflow deficits. This study analyzed the long-term variability and seasonality of low flows and streamflow droughts in fifteen headwater catchments of three regions within Central Europe. To quantify the changes in the low flow regime of selected catchments during the 1968–2019 period, we applied the R package lfstat for computing the seasonality ratio (SR), the seasonality index (SI), mean annual minima, as well as for the detection of streamflow drought events along with deficit volumes. Trend analysis of summer minimum discharges was performed using the Mann–Kendall test. Our results showed a substantial increase in the proportion of summer low flows during the analyzed period, accompanied with an apparent shift in the average date of low flow occurrence towards the start of the year. The most pronounced seasonality shifts were found predominantly in catchments with the mean altitude 800–1000 m.a.s.l. in all study regions. In contrast, the regime of low flows in catchments with terrain above 1000 m.a.s.l. remained nearly stable throughout the 1968–2019 period. Moreover, the analysis of mean summer minimum discharges indicated a much-diversified pattern in behavior of long-term trends than it might have been expected. The findings of this study may help identify the potentially most vulnerable near-natural headwater catchments facing worsening summer water scarcity.

Specific climate classification for Mediterranean hydrology and future evolution under Med-CORDEX regional climate model scenarios

The Mediterranean region is one of the most sensitive regions to anthropogenic and climatic changes, mostly affecting its water resources and related practices. With multiple studies raising serious concerns about climate shifts and aridity expansion in the region, this one aims to establish a new high-resolution classification for hydrology purposes based on Mediterranean-specific climate indices. This classification is useful in following up on hydrological (water resource management, floods, droughts, etc.) and ecohydrological applications such as Mediterranean agriculture. Olive cultivation is the characteristic agricultural practice of the Mediterranean region. The proposed approach includes the use of classic climatic indices and the definition of new climatic indices, mainly precipitation seasonality index Is or evapotranspiration threshold SPET, both in line with river flow regimes, a principal component analysis to reduce the number of indices, K-means classification to distribute them into classes, and finally the construction of a decision tree based on the distances to class kernels to reproduce the classification without having to repeat the whole process. The classification was set and validated by WorldClim-2 at 1 km high-resolution gridded data for the 1970–2000 baseline period and 144 stations' data over 30 to 120 years, both at monthly time steps. Climatic classes coincided with a geographical distribution in the Mediterranean ranging from the most seasonal and driest class 1 in the south to the least seasonal and most humid class 5 in the north, showing the climatic continuity from one place to another and enhancing the visibility of change trends. The MED-CORDEX ALADIN and CCLM historical and projected data at 12 and 50 km resolution simulated under the RCP4.5 and 8.5 scenarios for the 2070–2100 period served to assess the climate change impact on this classification by superimposing the projected changes on the baseline grid-based classification. RCP scenarios increase the seasonality index Is by +80 % and the aridity index IArid by +60 % in the north and IArid by +10 % without Is change in the south, hence causing the wet season shortening and river regime modification with the migration north of moderate and extreme winter regimes instead of early spring regimes. The ALADIN and CCLM regional climate models (RCMs) have demonstrated an evolution of the Mediterranean region towards arid climate. The classes located to the north are slowly evolving towards moderate coastal classes, which might affect hydrologic regimes due to shorter humid seasons and earlier snowmelts. These scenarios might look favourable for Mediterranean cultivation; however, the expected impact on water resources and flow regimes will surely expand and directly hit ecosystems, food, health, and tourism, as risk is interconnected between domains. This kind of classification might be reproduced at the global scale, using the same or other climatic indices specific to each region, highlighting their physiographic characteristics and hydrological responses.

Specific Climate Classification for Mediterranean Hydrology and Future Evolution Under Med-CORDEX RCM Scenarios

The Mediterranean is one of the most sensitive regions to anthropogenic and climatic changes mostly affecting its water resources and related practices. With multiple studies raising serious concerns of climate shifts and aridity expansion in the region, this one aims to establish a new high resolution classification for hydrology purposes based on Mediterranean specific climate indices. This classification is useful in following up hydrological (water resources management, floods, droughts, etc.), and ecohydrological applications such as Mediterranean agriculture like olive cultivation and other environmental practices. The proposed approach includes the use of classic climatic indices and the definition of new climatic indices mainly precipitation seasonality index Is or evapotranspiration threshold SPET both in line with river flow regimes, a Principal Component Analysis to reduce the number of indices, K-Means classification to distribute them into classes and finally the construction of a decision tree based on the distances to classes kernels to reproduce the classification without having to repeat the whole process. The classification was set and validated by WorldClim-2 at 1-km high resolution gridded data for the 1970–2000 baseline period and 144 stations data over 30 to 120 years, both at monthly time steps. Climatic classes coincided with a geographical distribution in the Mediterranean ranging from the most seasonal and dry class 1 in the south to the least seasonal and most humid class 5 in the North, showing up the climatic continuity from one place to another and enhancing the visibility of change trends. The MED-CORDEX ALADIN and CCLM historical and projected data at 12-km and 50-km resolution simulated under RCP 4.5 and 8.5 scenarios for the 2070–2100 period served to assess the climate change impact on this classification by superimposing the projected changes on the baseline grid based classification. RCP scenarios are increasing seasonality index Is by +80 % and aridity index IArid by +60 % in the North and IArid by +10 % without Is change in the South, hence causing the wet seasons shortening and river regimes modification with the migration North of winter moderate and extreme winter regimes instead of early spring regimes. ALADIN and CCLM RCM models have demonstrated an evolution of the Mediterranean region towards arid climate. The classes located to the north are slowly evolving towards moderate coastal classes which might affect hydrologic regimes due to shorter humid seasons and earlier snowmelts. These scenarios might look favourable for Mediterranean cultivation however, the expected impact on water resources and flow regimes will sure expand and directly hit ecosystems, food, health and tourism as risk is interconnected between domains. This kind of classification might be reproduced at the global scale, using same or other climatic indices specific for each region highlighting their physiographic characteristics and hydrological response.

How well does climate model perform for southern Brazil?

<p>Southern Brazil is in a transitional zone between tropical and extratropical climates. The rainfall regime in such transitional zones can be rather sensitive to climate change and related expansion of the tropics in the Southern Hemisphere. It is expected that rainfall will increase up to 30% over this area in the next decades. It is important, however, to investigate if the mechanisms that generate rainfall are simulated correctly in the models to know when downscaling and bias correction methods should be applied. The objective of this study is to evaluate the performance of the CMIP5 climate models in terms of precipitation in southern Brazil. This study addresses fundamental aspects of model evaluation and aims to give guidance on the proper use of climate model outputs for southern Brazil. We use 41 historical climate simulations and 22 RCP8.5 future climate simulations for the periods of 1980-2005 and 2070-2100, respectively. We compare the historical simulations with an interpolated product database obtained from ground stations. To evaluate the model performance regarding its marginal distribution, we use the following metrics: annual rainfall, variance, skewness, dry day fraction, wet day fraction, high percentiles and similarity of distributions (trough Kolmogorov-Smirnov test). There is a negative bias in all of them except for wet day fraction. All metrics of temporal aspects such as Markham’s seasonality index, autocorrelation, time of the annual maxima, dry spell average and maximum lengths, wet spell average and maximum lengths show a positive bias, apart from the time of annual maxima. Overall, annual rainfall is expected to increase in southern Brazil. Spatial patterns of annual rainfall are similar in the RCP 8.5 future pathways to the ones found in the historical period, with wetter areas expanding toward the north. However, the spatial pattern of observed rainfall is not captured by climate models. They simulate smaller volumes of precipitation in the southern border. A similar pattern was found in extreme precipitation, with bias almost twice as large than the one found in annual rainfall. Furthermore, the models do not properly represent the seasonal cycle, the Markham’s seasonality index reached four times the observed in some areas. Given the poor performance in the area, the use of future simulations in impact studies should be done carefully once the direct use of climate model precipitation in hydrological studies could result in misleading conclusions.</p><p>This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001</p>