Improving daily rainfall extremes simulation using the generalized Pareto distribution: a case study in Western Iran

Prediction of the occurrence or non-occurrence of daily rainfall plays a significant role in agricultural planning and water resource management projects. In this study, gamma distribution function (GDF), kernel, and exponential (EXP) distributions were coupled (piecewise) with a generalized Pareto distribution. Thus, the gamma-generalized Pareto (GGP), kernel-generalized Pareto (KGP), and exponential-generalized Pareto (EGP) models were used. The aim of the present study was to introduce new methods to modify the simulated generation of extreme rainfall amounts of rainy seasons based on the preserved spatial correlation. The best approach was identified using the normalized root mean square error (NRMSE) criterion. For this purpose, the 30-yr daily rainfall datasets of 21 synoptic weather stations located in different climates of West Iran were analyzed. The first, second, and third-order Markov chain (MC) models were used to describe rainfall time series frequencies. The best MC model order was detected using the Akaike information criterion and Bayesian information criterion. Based on the best identified MC model order, the best piecewise distribution models, and the Wilks approach, rainfall events were modeled with regard to the spatial correlation among the study stations. The performance of the Wilks approach was verified using the coefficient of determination. The daily rainfall simulation resulted in a good agreement between the observed and the generated rainfall data. Hence, the proposed approach is capable of helping water resource managers in different contexts of agricultural planning.

Sustainable management of populations impacted by harvesting and climate change

The sustainable use of natural resources is critical for addressing the global challenges of today. Strategies for sustainable harvesting need to consider not only harvested species, but also other non-harvested species interacting with them in the same ecosystem. In addition, environmental variation needs to be considered, with climate change currently being one of the main sources of this variation. Understanding the consequences of complex interactions between different drivers and processes affecting dynamics of species and ecosystems across spatial scales requires large-scale integrative research projects. The Norwegian research initiative “Sustainable management of renewable resources in a changing environment: an integrated approach across ecosystems” (SUSTAIN) was launched to fill knowledge gaps related to the sustainable management of populations and ecosystems experiencing climate change. SUSTAIN investigated terrestrial, marine and freshwater ecosystems in boreal and Arctic regions, using both theoretical developments and empirical analyses of long-term data. This Climate Research Special contains both synthesis articles and original research exemplifying some of the approaches used in SUSTAIN. In this introduction we highlight 4 key topics addressed by SUSTAIN: (i) population structure, (ii) interactions between species, (iii) spatial processes, and (iv) adaptive management. These topics are fundamental to the understanding of harvested species from an ecosystem perspective, and to ecosystem-based management approaches, which we are striving to work towards.

Changes in wind erosion climatic erosivity in northern China from 1981-2016: a comparison of two climate/weather factors of wind erosion models

Wind erosion is largely determined by wind erosion climatic erosivity. In this study, we examined changes in wind erosion climatic erosivity during 4 seasons across northern China from 1981-2016 using 2 models: the wind erosion climatic erosivity of the Wind Erosion Equation (WEQ) model and the weather factor from the Revised Wind Erosion Equation (RWEQ) model. Results showed that wind erosion climatic erosivity derived from the 2 models was highest in spring and lowest in winter with high values over the Kumtag Desert, the Qaidam Basin, the boundary between Mongolia and China, and the Hulunbuir Sandy Land. In spring and summer, wind erosion climatic erosivity showed decreasing trends in whole of northern China from 1981-2016, whereas there was an increasing trend in wind erosion climatic erosivity over the Gobi Desert from 1992-2011. For the weather factor of the RWEQ model, the difference between northern Northwest China and the Gobi Desert and eastern-northern China was much larger than that of the wind erosion climatic erosivity of the WEQ model. In addition, in contrast to a decreasing trend in the weather factor of the RWEQ model over southern Northwest China during spring and summer from 1981-2016, the wind erosion climatic erosivity of the WEQ model showed a decreasing trend for 1981-1992 and an increasing trend for 1992-2011 over southern Northwest China. According to a comparison between dust emission and wind erosion climatic erosivity, the 2 models have the ability to project changes in future wind erosion in northern China.

Tree ring-reconstructed late summer moisture conditions, 1546 to present, northern Lake Michigan, USA

Drought can affect even humid regions like northeastern North America, which experienced significant, well-documented dry spells in the 1930s, 50s, 60s, and 80s, and proxies tell us that in the years before instrumentally recorded climate, droughts could be even more severe. To get a more complete picture of pre-recorded climate, the spatial coverage of proxy-based climate reconstructions must be extended. This can better put in context past, current, and future climate, and it can lend anthropological and historical insights. With regard to tree rings as climate proxies, however, there is increasing evidence that relationships between tree growth and climate can be inconsistent over time, in some cases decreasing the utility of tree rings in the representation of climate. We developed a chronology from white cedar Thuja occidentalis tree ring widths for the period 1469-2015 C.E. with which we modeled the relationship between growth and July-September moisture conditions (Palmer Z index). The relationship was consistent across the period of instrumentally recorded climate, 1895-present, and the model explained 27% of variability. Therefore, we used the model to reconstruct July-September moisture conditions from 1546-2014. We found the most variable century to be the 20th, the least the 18th. The severest decade-scale droughts (≤0.75 SD from mean) occurred in the 1560s, 1600s/10s, 1630s, 1770s/80s, 1840s, and 1910s/20s, the severest pluvials (≥0.75 SD) in the 1610s/20s, 1660s/70s, and the 1970s/80s. The occasional occurrence of severe droughts throughout the reconstruction, increasing variability in the 20th century, and expected climate change-enhanced late summer drought, portend a future punctuated with severe droughts.