Global hydroclimatic response to tropical volcanic eruptions over the last millennium.

Large tropical volcanic eruptions can affect the climate of many regions on Earth, yet it is uncertain how the largest eruptions over the past millennium may have altered Earth's hydroclimate. Here, we analyze the global hydroclimatic response to all the tropical volcanic eruptions over the past millennium that were larger than the Mount Pinatubo eruption of 1991. Using the Paleo Hydrodynamics Data Assimilation product (PHYDA), we find that these large volcanic eruptions tended to produce dry conditions over tropical Africa, Central Asia and the Middle East and wet conditions over much of Oceania and the South American monsoon region. These anomalies are statistically significant, and they persisted for more than a decade in some regions. The persistence of the anomalies is associated with southward shifts in the Intertropical Convergence Zone and sea surface temperature changes in the Pacific and Atlantic oceans. We compare the PHYDA results with the stand-alone model response of the Community Earth System Model (CESM)-Last Millennium Ensemble. We find that the proxy-constrained PHYDA estimates are larger and more persistent than the responses simulated by CESM. Understanding which of these estimates is more realistic is critical for accurately characterizing the hydroclimate risks of future volcanic eruptions.

Genetic association with high-resolution climate data reveals selection footprints in the genomes of barley landraces across the Iberian Peninsula.

Landraces are local populations of crop plants adapted to a particular environment. Extant landraces are surviving genetic archives, keeping signatures of the selection processes experienced by them until settling in their current niches. This study intends to establish relationships between genetic diversity of barley (Hordeum vulgare L.) landraces collected in Spain and the climate of their collection sites. A high-resolution climatic data set (5 × 5 km spatial, 1-day temporal grid) was computed from over 2,000 temperature and 7,000 precipitation stations across peninsular Spain. This data set, spanning the period 1981-2010, was used to derive agroclimatic variables meaningful for cereal production at the collection sites of 135 barley landraces. Variables summarize temperature, precipitation, evapotranspiration, potential vernalization and frost probability at different times of the year and time scales (season and month). SNP genotyping of the landraces was carried out combining Illumina Infinium assays and genotyping-by-sequencing, yielding 9,920 biallelic markers (7,479 with position on the barley reference genome). The association of these SNPs with agroclimatic variables was analysed at two levels of genetic diversity, with and without taking into account population structure. The whole data sets and analysis pipelines are documented and available at https://eead-csic-compbio.github.io/barley-agroclimatic-association. We found differential adaptation of the germplasm groups identified to be dominated by reactions to cold temperature and late-season frost occurrence, as well as to water availability. Several significant associations pointing at specific adaptations to agroclimatic features related to temperature and water availability were observed, and candidate genes underlying some of the main regions are proposed.

SiCLIMA: High-resolution hydroclimate and temperature dataset for Aragón (northeast Spain).

A new high-resolution climatic gridded dataset was built for Aragón (northeast Spain) using a large collection of daily precipitation and temperature observations from more than 3000 weather stations. The grid covers, at the unprecedented spatial resolution of 0.25 km2, daily maximum and minimum temperatures and precipitation in the 1950-2020 period. The complex orography (from 70 to 3,400 m.a.s.l.) of the medium-sized region (∼48,000 km2) required a climate modelling method based on a spatially-dense weather monitoring network and local predictors. The 3-step workflow for grid creation consisted of: 1) a comprehensive quality control of raw observations, based on a spatial comparison with nearest data; 2) a climate reconstruction based on the creation of reference values, through multivariate linear regressions, for every day and location, based on the observed climate and terrain-based environmental variables; and 3) the prediction of precipitation and temperature values in a regular 500 × 500 m grid, based on the reconstructed data series. The resulting dataset improves the spatial representativity of climate and allows for a detailed analyses at landscape scale not only in climate studies but also in related disciplines such as hydrology or biogeography, amongst others.

Climate of the Pyrenees: Extremes indices and long-term trends.

We utilized an extensive, multisource, cross-border dataset of daily meteorological observations from over 1500 stations in the Pyrenees, spanning from the mid-20th century to 2020, to examine the spatial and temporal climate patterns. Our focus was on 17 indices related to extreme precipitation and temperature events across the mountain range. The original data underwent rigorous quality control and homogenization processes, employing a comprehensive workflow that included spatial modeling based on environmental predictors. This process yielded two main outcomes: 1) a high-resolution gridded dataset (1 km2) of daily precipitation, maximum and minimum temperature from 1981 to 2020, allowing for a detailed analysis of spatial variations; and 2) an evaluation of long-term annual and seasonal trends from 1959 to 2020, using selection of high-quality data series that were homogenized to preserve their temporal structure and coherence. The findings revealed a clear elevation-related pattern in temperature indices (with the exception of tropical nights, which were predominantly observed on the Mediterranean side) and a distinct north-south latitudinal disparity in precipitation, turning longitudinal when focusing on extreme precipitation events. Overall, there was a notable and significant warming trend of 0.2 to 0.4 °C per decade, and a non-significant change of precipitation, with the exception of the southern and Mediterranean regions, where there was a notable decrease, approximately -3 % per decade, observed on an annual basis.

A new long term gridded daily precipitation dataset at high-resolution for Cuba (CubaPrec1).

The paper presents a high-resolution (-3km) gridded dataset for daily precipitation across Cuba for 1961-2008, called CubaPrec1. The dataset was built using the information from the data series of 630 stations from the network operated by the National Institute of Water Resources. The original station data series were quality controlled using a spatial coherence process of the data, and the missing values were estimated on each day and location independently. Using the filled data series, a grid of 3 × 3 km spatial resolution was constructed by estimating daily precipitation and their corresponding uncertainties at each grid box. This new product represents a precise spatiotemporal distribution of precipitation in Cuba and provides a useful baseline for future studies in hydrology, climatology, and meteorology. The data collection described is available on zenodo: https://doi.org/10.5281/zenodo.7847844.

Dominance of Fagus sylvatica in the Growing Stock and Its Relationship to Climate-An Analysis Using Modeled Stand-Level Climate Data.

In the future, climate change is expected to affect the spatial distribution of most tree species in Europe. The European beech (Fagus sylvatica), a drought-sensitive tree species, is currently distributed throughout Europe, where it is an ecologically and economically important species. In Slovenia, the European beech represents 33% of the growing stock, but such a proportion greatly varies across Europe. Whether such a variation is related to the climate environmental gradients or because of historical or management decisions is an as-yet unexplored question. For this study, we employed the Slovenian Forests Service inventory, where the proportion of beech in the forest stock has been monitored in 341,341 forest stands across the country. Modeled climate data from the SLOCLIM database, calculated for each of the stands, was also used to test the hypothesis that although beech forests have always been influenced by human activity, the dominance of beech trees in forest stands is at least partially dictated by the climate. The results showed the distribution of the main climate variables (annual precipitation, the share of summer and spring precipitation, and annual maximum and minimum temperatures) and how they affect the current dominance of beech trees at the stand level. Due to the large number and variability of forest stands studied, the results should be transferable to better understand and manage the climatic suitability and risks of Fagus sylvatica. The modeled data is publicly available in the web repository Zenodo.

Socioeconomic inequalities and the surface heat island distribution in Santiago, Chile.

Surface urban heat islands (SUHIs) are an important socio-environmental problem associated with large cities, such as the Santiago Metropolitan Area (SMA), in Chile. Here, we analyze daytime and nighttime variations of SUHIs for each season of the year during the period 2000-2020. To evaluate socioeconomic inequities in the distribution of SUHIs, we establish statistical relationships with socioeconomic status, land price, and urban vegetation. We use the MODIS satellite images to obtain the land surface temperatures and the normalized difference vegetation index (NDVI) through the Google Earth Engine platform. The results indicate more intense SUHIs during the nighttime in the eastern sector, coinciding with higher socioeconomic status and larger green areas. This area during the day is cooler than the rest of the city. The areas with lower and middle socioeconomic status suffer more intense SUHIs (daytime and nighttime) and match poor environmental and urban qualities. These results show the high segregation of SMA. Urban planning is subordinated to land prices with a structure maintained over the study period. The lack of social-climate justice is unsustainable, and such inequalities may be exacerbated in the context of climate change. Thus, these results can contribute to the planning of the SMA.

Climate-change-driven growth decline of European beech forests.

The growth of past, present, and future forests was, is and will be affected by climate variability. This multifaceted relationship has been assessed in several regional studies, but spatially resolved, large-scale analyses are largely missing so far. Here we estimate recent changes in growth of 5800 beech trees (Fagus sylvatica L.) from 324 sites, representing the full geographic and climatic range of species. Future growth trends were predicted considering state-of-the-art climate scenarios. The validated models indicate growth declines across large region of the distribution in recent decades, and project severe future growth declines ranging from -20% to more than -50% by 2090, depending on the region and climate change scenario (i.e. CMIP6 SSP1-2.6 and SSP5-8.5). Forecasted forest productivity losses are most striking towards the southern distribution limit of Fagus sylvatica, in regions where persisting atmospheric high-pressure systems are expected to increase drought severity. The projected 21st century growth changes across Europe indicate serious ecological and economic consequences that require immediate forest adaptation.

Recent wildfires in Central Chile: Detecting links between burned areas and population exposure in the wildland urban interface.

Wildfires are gaining importance in the Mediterranean regions owing to climate change and landscape changes due to the increasing closeness between urban areas and forests prone to wildfires. We analysed the dry season wildfire occurrences in the Mediterranean region of Central Chile (32°S-39°30' S) between 2000 and 2017, using satellite images to detect burned areas, their landscape metrics and the land use and covers (vegetal) pre-wildfire, in order to determine the population living in areas that may be affected by wildfires. The existing regulations in western Mediterranean countries (Portugal, Spain, France, and Italy) were used to identify and define the wildland-urban interface (WUI) areas, quantifying the people inhabiting them and estimating the population affected by burned areas from 2001 to 2017. We used the Google Earth Engine to process MODIS products and extract both burned areas and land covers. We detected that 25% of the urban population inhabits WUI areas (i.e. Biobío, Araucanía and Valparaíso regions) where the urban population exposed to burned areas exceeds 40%. Most of the land use and land covers affected by wildfires are anthropogenic land covers, classified as savannas, croplands, evergreen broadleaf forests and woody savannas, representing >70% of the burned areas. Urban areas show only 0.6% of the burned surface from 2001 to 2017. We estimate that 55,680 people are potentially affected by wildfires, and 50% of them are in just one administrative region. These results show the imperative need for public policies as a regulating force for establishing WUI areas with the purpose of identifying wildfire risk in urban areas, such as establishing prevention methods as firewalls and prescribed fires.

Computation of rainfall erosivity from daily precipitation amounts.

Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases.

Missing Rings in Pinus halepensis - The Missing Link to Relate the Tree-Ring Record to Extreme Climatic Events.

Climate predictions for the Mediterranean Basin include increased temperatures, decreased precipitation, and increased frequency of extreme climatic events (ECE). These conditions are associated with decreased tree growth and increased vulnerability to pests and diseases. The anatomy of tree rings responds to these environmental conditions. Quantitatively, the width of a tree ring is largely determined by the rate and duration of cell division by the vascular cambium. In the Mediterranean climate, this division may occur throughout almost the entire year. Alternatively, cell division may cease during relatively cool and dry winters, only to resume in the same calendar year with milder temperatures and increased availability of water. Under particularly adverse conditions, no xylem may be produced in parts of the stem, resulting in a missing ring (MR). A dendrochronological network of Pinus halepensis was used to determine the relationship of MR to ECE. The network consisted of 113 sites, 1,509 trees, 2,593 cores, and 225,428 tree rings throughout the distribution range of the species. A total of 4,150 MR were identified. Binomial logistic regression analysis determined that MR frequency increased with increased cambial age. Spatial analysis indicated that the geographic areas of south-eastern Spain and northern Algeria contained the greatest frequency of MR. Dendroclimatic regression analysis indicated a non-linear relationship of MR to total monthly precipitation and mean temperature. MR are strongly associated with the combination of monthly mean temperature from previous October till current February and total precipitation from previous September till current May. They are likely to occur with total precipitation lower than 50 mm and temperatures higher than 5°C. This conclusion is global and can be applied to every site across the distribution area. Rather than simply being a complication for dendrochronology, MR formation is a fundamental response of trees to adverse environmental conditions. The demonstrated relationship of MR formation to ECE across this dendrochronological network in the Mediterranean basin shows the potential of MR analysis to reconstruct the history of past climatic extremes and to predict future forest dynamics in a changing climate.