A daily reconstruction of historical weather to study past climate variability and impacts

Studying daily weather of the past can provide relevant insights into the decadal variability of weather events and climate impacts that are not resolved in current climate reconstructions. While monthly to seasonal reconstructions have been evaluated for the past several hundred years, the daily time scale has received little attention, mainly because the necessary data sets are scarce. In this thesis, a daily reconstruction of high-resolution (1x1 km²) temperature and precipitation fields from 1763 to 1960 is presented, that forms together with present-day fields a 258-year-long gridded data set for Switzerland (Chapter 2). Further, reconstructions for sea level pressure and temperature for several short periods in the late 18ᵗʰ and early 19ᵗʰ century for Europe are presented (Sect. 1.3 and Appendix A). These data sets allow for new analyses of daily weather and daily-based climate indices that were hitherto not possible. The meteorological fields were reconstructed using the Analogue Resampling Method (ARM) to generate a first guess of the meteorological fields, and subsequently improved by assimilating temperature and pressure observations and bias-correcting precipitation fields. For Switzerland, cross-validation results of the temperature reconstruction show good skill even for the very early periods before 1864, when observations were sparse. The reconstruction skill for precipitation is lower than for temperature, but wet days frequencies compare well to independent observations. Based on this gridded data set, we calculated climate indices and two phenological phases to evaluate spring weather over the 258-year-long period (Chapter 3). Although it receives less attention than winter and summer, the spring season is important because adverse weather conditions in spring delay plant growth, and late frosts can damage vegetation. Climate and phenological indices impressively depict the warming of the recent decades compared to the pre-industrial reference period 1871 to 1900. Cherry flowering, for example, advanced by up to 20 days in the Swiss Plateau since the pre-industrial reference period. In the 258-year-long series, the spring of 1785 stands out of the reconstruction with a mean temperature of only 4.10 °C and up to 30 days of frost registered in the Swiss Plateau. Further data sets and historical sources confirm that this was a record-breaking cold spring, with prolonged inversion conditions in the Swiss Plateau. Among the ten warmest summer half years in Switzerland, only one summer from the 20ᵗʰ century remains, the summer of 1947 (Chapter 4). It still ranks as the fifth warmest summer on record based on a time series for the Swiss Plateau since 1756. In some parts of Switzerland, precipitation deficits are still the lowest since 1864. The repeated occurrence of blocking anticyclones led to a total of five heat waves in some parts of Switzerland between May and September, contributing to the anomalously warm temperatures. The warm and dry conditions had severe consequences such as extensive glacier ice loss, drying out of lakes, and forest damage. If we compare the warm summers to their mean climatic state, the summer of 1947 was indeed as extreme as 2003. However, the summer of 2022, the second warmest summer on record, was a fairly normal summer compared to its mean climate. Compared to the summer temperatures expected by the end of the century (2070 - 2099), the record summers of 1947, 2003, and 2022 would only be fairly normal summers under an emissions reduction scenario (RCP2.6), and such summers would be exceptionally cold if no emissions reductions are achieved (RCP8.5)

Statistical reconstruction of daily temperature and sea level pressure in Europe for the severe winter 1788/89

The winter 1788/89 was one of the coldest winters Europe had witnessed in the past 300 years. Fortunately, for historical climatologists, this extreme event occurred at a time when many stations across Europe, both private and as part of coordinated networks, were making quantitative observations of the weather. This means that several dozen early instrumental series are available to carry out an indepth study of this severe cold spell. While there have been attempts to present daily spatial information for this winter, there is more to be done to understand the weather variability and day-to-day processes that characterised this weather extreme. In this study, we seek to reconstruct daily spatial high-resolution temperature and sea level pressure fields of the winter 1788/89 in Europe from November through February. The reconstruction is performed with an analogue esampling method (ARM) that uses both historical instrumental data and a weather type classification. Analogue reconstructions are then post-processed through an ensemble Kalman fitting (EnKF) technique. Validation experiments show good skill for both reconstructed variables, which manage to capture the dynamics of the extreme in relation to the large-scale circulation. These results are promising for more such studies to be undertaken, focusing on different extreme events and other regions in Europe and perhaps even further back in time. The dataset presented in this study may be of sufficient quality to allow historians to better assess the environmental and social impacts of the harsh weather

The rainy season in the Southern Peruvian Andes: A climatological analysis based on the new Climandes index

The rainy season is of high importance for livelihoods in the Southern Peruvian Andes (SPA), especially for agriculture, which is mainly rain fed and one of the main income sources in the region. Therefore, knowledge and predictions of the rainy season such as its onset and ending are crucial for planning purposes. However, such information is currently not readily available for the local population. Moreover, an evaluation of existing rainy season indices shows that they are not optimally suited for the SPA and may not be directly applicable in a forecasting context. Therefore, we develop a new index, named Climandes index, which is tailored to the SPA and designed to be of use for operational monitoring and forecasting purposes. Using this index, we analyse the climatology and trends of the rainy season in the SPA. We find that the rainy season starts roughly between September and January with durations between 3 and 8 months. Both onset and duration show a pronounced northeast-southwest gradient, regions closer to the Amazon Basin have a considerably longer rainy season. The inter-annual variability of the onset is very high, that is, 2–5 months depending on the station, while the end of the rainy season shows a much lower variability (i.e., 1.5–3 months). The spatial patterns of total precipitation amount and dry spells within the rainy season are only weakly related to its timing. Trends in rainy season characteristics since 1965 are mostly weak and not significant, but generally indicate a tendency towards a shortening of the rainy season in the whole study area due to a later onset and an increase in precipitation sums during the rainy season in the northwestern study area

A combined view on precipitation and temperature climatology and trends in the southern Andes of Peru

In the southern Peruvian Andes, communities are highly dependent on climatic conditions due to the mainly rain-fed agriculture and the importance of glaciers and snow melt as a freshwater resource. Longer-term trends and year-to-year variability of precipitation or temperature severely affect living conditions. This study evaluates seasonal precipitation and temperature climatologies and trends in the period 1965/66–2017/18 for the southern Peruvian Andes using quality-controlled and homogenized station data and new observational gridded data. In this region, precipitation exhibits a strong annual cycle with very dry winter months and most of the precipitation falling from spring to autumn. Spatially, a northeast–southwest gradient in austral spring is observed, related to an earlier start of the rainy season in the northeastern partof the study area. Seasonal variations of maximum temperature are weak withan annual maximum in austral spring, which is related to reduced cloud coverin austral spring compared to summer. On the contrary, minimum tempera-tures show larger seasonal variations, possibly enhanced through changes inlongwave incoming radiation following the precipitation cycle. Precipitationtrends since 1965 exhibit low spatial consistency except for austral summer,when in most of the study area increasing precipitation is observed, and in aus-tral spring, when stations in the central-western region of the study area regis-ter decreasing precipitation. All seasonal and annual trends in maximum temperature are larger than trends in minimum temperature. Maximum temperature exhibits strong trends in austral winter and spring, whereas minimum temperature trends are strongest in austral winter. We hypothesize, that these trends are related to precipitation changes, as decreasing (increasing) precipita-tion in spring (summer) may enhance maximum (minimum) temperature trends through changes in cloud cover. El Niño Southern Oscillation (ENSO), however, has modifying effects onto precipitation and temperature, and thereby leads to larger trends in maximum temperatures

High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

Gridded high-resolution climate datasets are increasingly important for a wide range of modelling applications. Here we present PISCOt (v1.2), a novel high spatial resolution (0.01°) dataset of daily air temperature for entire Peru (1981–2020). The dataset development involves four main steps: (i) quality control; (ii) gap-filling; (iii) homogenisation of weather stations, and (iv) spatial interpolation using additional data, a revised calculation sequence and an enhanced version control. This improved methodological framework enables capturing complex spatial variability of maximum and minimum air temperature at a more accurate scale compared to other existing datasets (e.g. PISCOt v1.1, ERA5-Land, TerraClimate, CHIRTS). PISCOt performs well with mean absolute errors of 1.4 °C and 1.2 °C for maximum and minimum air temperature, respectively. For the first time, PISCOt v1.2 adequately captures complex climatology at high spatiotemporal resolution and therefore provides a substantial improvement for numerous applications at local-regional level. This is particularly useful in view of data scarcity and urgently needed model-based decision making for climate change, water balance and ecosystem assessment studies in Peru

Daily high-resolution temperature and precipitation fields for Switzerland from 1763 to 2020

This dataset provides high-resolution (1km x 1km), daily reconstructions of temperature and precipitation fields for Switzerland from 1763 to 2020. The fields are reconstructed using the analog resampling method and subsequent data assimilation for temperature and quantile mapping for precipitation. The dataset consists of two subperiod: (1) an update of the reconstructions provided by Pfister (2019) (doi:10.1594/PANGAEA.907579) for the period 1864 to 2020 with the higher resolution grid and extending to 2020, and (2) a new reconstruction for the period 1763 to 1863 for which so far no reconstruction exists. The dataset from 1864 to 2020 is reconstructed based on observational data from the Swiss meteorological service with a high quality and dense station network. The reconstruction for the early period from 1763 to 1863, is based on early instrumental measurements of temperature, pressure, and precipitation, that have been rescued in various projects. Observations entering the reconstruction for the early period are much more scarce and their quality is lower. We recommend to notice this when using the reconstructions. For further information, please refer to the references

Extreme springs in Switzerland since 1763 in climate and phenological indices

Historical sources report manifold on hazardous past climate and weather events that had considerable impacts on society. Studying changes in the occurrence or mechanisms behind such events is, however, hampered by a lack of spatially and temporally complete weather data. In particular, the spring season has received less attention in comparison to summer and winter but is nevertheless relevant, since weather conditions in spring can delay vegetation and create substantial damage due to late-frost events. For Switzerland, we created a daily high-resolution (1 × 1 km2) reconstruction of temperature and precipitation fields from 1763 to 1960 that forms, together with present-day meteorological fields, a 258-year-long gridded data set. With this data set, we study changes in long-term climate and historical weather events based on climate and phenological indices focusing on the spring season. Climate and phenological indices show few changes in the mean during the first 200 years compared to the most recent period from 1991 to 2020, where climate change signals clearly emerged in many indices. We evaluate the climate and phenological indices for three cases of extreme spring weather conditions: an unusually warm spring, two late-frost events, and three cold springs. Warm springs are much more frequent in the 21st century, but a very warm and early spring also occurred in 1862. Spring temperatures, however, do not agree on how anomalously warm the spring was when comparing the Swiss temperature reconstruction with reanalyses that extend back to 1868. The three springs of 1785, 1837, and 1853 were particularly cold, with historical sources reporting, for example, prolonged lake freezing and abundant snowfall. Whereas the springs of 1837 and 1853 were characterized by cold and wet conditions, in the spring of 1785 wet days were below average, and frost days reached an all-time maximum, in particular in the Swiss Plateau, indicating inversion conditions. Such conditions are in line with a high occurrence of northeasterly and high-pressure weather types and historical sources describing Bise conditions, a regional wind in the Alpine area related to inversions. Studying such historical events is valuable, since similar atmospheric conditions can lead to cold springs affecting vegetation growth and agricultural production