Hail has been identified as the largest contributor to insured losses from thunderstorms globally, with losses costing the insurance industry billions of dollars each year. Yet, of all precipitation types, hail is probably subject to the largest uncertainties. Some might go so far as to argue that observing and forecasting hail is as difficult, if not more difficult, than is forecasting tornadoes. The reasons why hail is challenging are many and varied and reflected by the fact that hailstones display a wide variety of shapes, sizes and internal structures. There is also an important clue in this diversity—nature is telling us that hail can grow by following a wide variety of trajectories within thunderstorms, each having a unique set of conditions. It is because of this complexity that modeling hail growth and forecasting size is so challenging. Consequently, it is understandable that predicting the occurrence and size of hail seems an impossible task. Through persistence, ingenuity and technology, scientists have made progress in understanding the key ingredients and processes at play. Technological advances mean that we can now, with some confidence, identify those storms that very likely contain hail and even estimate the maximum expected hail size on the ground hours in advance. Even so, there is still much we need to learn about the many intriguing aspects of hail growth.
Climate data support a suite of scientific and socioeconomic activities that can reinforce development gains and improve the lives of those most vulnerable to climate variability and change. Historical and current weather and climate observations are essential for many activities, including operational meteorology, identifying extreme events and assessing associated risks, developing climate-informed early warning systems, planning, and research. Rainfall is the most widely available and used climate variable. Thus, measurement of rainfall is crucial to society’s well-being. In general, measurements from ground meteorological stations managed by National Meteorological Agencies are the principal sources of rainfall data. The main strength of the station observations is that they are assumed to give the “true” measurements of rainfall. However, the distribution of the meteorological observation network over Africa is significantly inadequate, with declining numbers of stations and poor data quality. This problem is compounded by the fact that the distribution of existing stations is uneven, with most weather stations located in cities and towns along major roads. As a result, coverage tends to be worse in rural areas, where livelihoods may be most vulnerable to climate variability and change. This has resulted in critical gaps in the provision of climate services where it is needed the most. Space-based measurements from satellites are being used as a complement to or in place of ground observations. Satellite-derived precipitation estimates offer good spatial coverage and improved temporal and spatial resolution, as well as near-real-time availability. Moreover, a range of satellite rainfall products are freely available from many sources, and a couple of these products are available only for Africa. However, satellite rainfall products also suffer from many shortcomings that include accuracy, particularly at higher temporal resolutions; coarse spatial resolution; short time series; and temporal inhomogeneity due to varying inputs. This limits the use of the use these products for certain applications. Understanding satellite rainfall estimation errors is critical for deciding which products might be used for specific applications and requires rigorous evaluation of these products using ground observations. The challenge in Africa is lack of availability, accessibility, and quality of rain-gauge observations that could be used for this purpose. Despite these challenges, there have been some validation efforts over different parts of the continent. However, different and inconsistent approaches of validation have created challenges to using these evaluation results. A comprehensive validation of the main operational satellite products at a continental level is needed to overcome these challenges and make the best use of satellite rainfall products in different applications.
Phenology is the study of the seasonal timing of life cycle events. The Belgian botanist Charles Morren introduced the term in 1853, which is a combination of two Greek words, φαίνω, which means to show, to bring to light, make to appear, and λόγος, which means study, discourse, or reasoning. The global change discussion has stimulated phenological research, which as a consequence greatly advanced as science and evolved to one of the main climate impact indicators. Many of the earliest systematic efforts to collect phenological observations took place in countries sharing the Alps, most of which are still operating phenological networks. These phenological data sets are generally freely available to researchers, and numerous essential contributions to the topic of phenology and climate have been built on those data sets. Plant physiological processes underlying the ability of the plants to adapt to the year-to-year variability of the climate still constitutes largely a black box. Since the experiments of René Antoine Ferchault de Reaumur in the 18th century, it is known that temperature constitutes the main environmental driver of the seasonal development of the mid- to high-latitude plants. Second to temperature, day length governs the seasonal cycle of some species as an additional factor. Therefore, temperature-driven phenological models are able to simulate the year-to-year variability of phenological entry dates accurately enough for various applications, such as climate change impact research or numerical pollen forecast models, where the beginning of flowering of some plants is linked with the release of allergic pollen into the atmosphere. Large-scale circulation patterns, like the North Atlantic Oscillation, determine the frequency and intensity of warm and cold spells and decadal temperature trends over Europe. Combined anthropogenic and natural forcings explain the advance of spring phenology over the last 50 years, which is also clearly discernible in the area of the Alps. The early phenological spring starts in Western Europe, whereas later in the season it makes progress with a stronger southerly component across the Alps. The combined temporal and spatial trends have been studied along elevational gradients. Trends toward earlier entry dates are stronger at higher elevations, which indicates that the elevational phenological gradient has weakened since the mid-20th century. Similarly, the vegetation response to temperature is observed to decrease when moving from high to low latitudes. In contrast, the temporal response of plant phenology to increasing temperatures is less clear. Some works indeed demonstrate a decreasing temperature sensitivity with increasing temperature, which is explained as a result of a reduced winter chilling that delays spring phenology or of a limiting effect due to a shorter photoperiod. Other works report no change of temporal temperature sensitivity with increasing temperatures. Indigenous midlatitude vegetation is able to withstand large temperature variations during winter and spring. The safety margin between last frost events, budding, and leaf emergence was found to be uniform across elevations and taxa, except for beech trees. The probability of freezing damage to natural vegetation is almost nil, but late frost risk constitutes a real threat to fruit growers. The ratio of phenological and last frost trends is ambiguous. An increase or decrease in frost risk depends on regions, elevations, and species. Vegetation at high altitudes is exposed to a harsh climate with a long-lasting snow cover, low temperatures, and a short growing season. Snowmelt is a necessary but insufficient requirement for the start of the growing season, which has to be supplemented by plant-specific temperature sums to activate the growth of most alpine and subalpine species. The seasonal cycle has to be completed within a short time. Advances in remote sensing technology have provided access to high-resolution landscape scale phenological information. Especially in remote areas, like the Alps, in situ observations could be supplemented by satellite observations. Observations from both methods, I -situ and remote sensing, have been applied to describe spring vegetation dynamics, but the correlation between these data sets have typically been weak because of differences in temporal and spatial scales and resolutions. A successfully combined description of the seasonal vegetation cycle is still lacking. The area of the European Alps offers a wealth of long chronicles, containing historical phenological observations some of which have been extracted and digitized. Grape harvest dates belong to the most readily available historical phenological observations, which have helped reconstruct summer temperatures as far back as the 15th century.
Rasmus Fensholt, Cheikh Mbow, Martin Brandt, and Kjeld Rasmussen
In the past 50 years, human activities and climatic variability have caused major environmental changes in the semi-arid Sahelian zone and desertification/degradation of arable lands is of major concern for livelihoods and food security. In the wake of the Sahel droughts in the early 1970s and 1980s, the UN focused on the problem of desertification by organizing the UN Conference on Desertification (UNCOD) in Nairobi in 1976. This fuelled a significant increase in the often alarmist popular accounts of desertification as well as scientific efforts in providing an understanding of the mechanisms involved. The global interest in the subject led to the nomination of desertification as focal point for one of three international environmental conventions: the UN Convention to Combat Desertification (UNCCD), emerging from the Rio conference in 1992. This implied that substantial efforts were made to quantify the extent of desertification and to understand its causes. Desertification is a complex and multi-faceted phenomenon aggravating poverty that can be seen as both a cause and a consequence of land resource depletion. As reflected in its definition adopted by the UNCCD, desertification is “land degradation in arid, semi-arid[,] and dry sub-humid areas resulting from various factors, including climate variation and human activities” (UN, 1992). While desertification was seen as a phenomenon of relevance to drylands globally, the Sahel-Sudan region remained a region of specific interest and a significant amount of scientific efforts have been invested to provide an empirically supported understanding of both climatic and anthropogenic factors involved. Despite decades of intensive research on human–environmental systems in the Sahel, there is no overall consensus about the severity of desertification and the scientific literature is characterized by a range of conflicting observations and interpretations of the environmental conditions in the region. Earth Observation (EO) studies generally show a positive trend in rainfall and vegetation greenness over the last decades for the majority of the Sahel and this has been interpreted as an increase in biomass and contradicts narratives of a vicious cycle of widespread degradation caused by human overuse and climate change. Even though an increase in vegetation greenness, as observed from EO data, can be confirmed by ground observations, long-term assessments of biodiversity at finer spatial scales highlight a negative trend in species diversity in several studies and overall it remains unclear if the observed positive trends provide an environmental improvement with positive effects on people’s livelihood.