Potential for long-range regional precipitation prediction over India

The potential for long-range precipitation prediction over the Indian monsoon region is generally good where climate noise (i.e., variability due to daily weather fluctuations) is small as compared to the climate signal (i.e., variability due to year to year fluctuations in monthly/seasonal means) being in the tropical belt. In order to understand the potential on smaller spatial scales, the ratios of inter-annual variability to that associated with climate noise have been computed for precipitation of four seasons as well as SW monsoon sub-seasons/months over 1656 stations in the Indian subcontinent. Precipitation in SW monsoon has been found potentially predictable on seasonal as well as intra-seasonal scale. The west coast and contiguous northwest India, part of the 'northeast India are more predictable. Potential for long-range prediction over northwest India is highest during the active monsoon period from July to September. Over eastern peninsula potential for prediction is generally found low whereas over north-central India it is always moderate. Over northern latitudes precipitation due to western disturbances during January to May is potentially predictable. Precipitation over southeast India and Sri Lanka during October to February due to northeast (NE) monsoon shows good potential for long-range prediction. It is manifested that long-range precipitation forecasting schemes for SW monsoon season, sub-seasons and months and for the other seasons over India on point to regional scale have good scope by taking into account the potential predictability at the individual stations as well as at contiguous resemblance areas over the country.

Observing the climate impact of large wildfires on stratospheric temperature

Wildfires are expected to become more frequent and intense in the future. They not only pose a serious threat to humans and ecosystems, but also affect Earth’s atmosphere. Wildfire plumes can reach into the stratosphere, but little is known about their climate impact. Here, we reveal observational evidence that major wildfires can have a severe impact on the atmospheric temperature structure and short-term climate in the stratosphere. Using advanced satellite observation, we find substantial warming of up to 10 K of the lower stratosphere within the wildfire plumes during their early development. The short-term climate signal in the lower stratosphere lasts several months and amounts to 1 K for the Northern American wildfires in 2017, and up to striking 3.5 K for the Australian wildfires in 2020. This is stronger than any signal from recent volcanic eruptions. Such extreme events affect atmospheric composition and climate trends, underpinning their importance for future climate.

Exploring the role of snow metamorphism on the isotopic composition of the surface snow at EastGRIP

Stable water isotopes from polar ice cores are invaluable high-resolution climate proxy records. Recent studies have aimed to improve knowledge of how the climate signal is stored in the water isotope record by addressing the influence of post-depositional processes on the surface snow isotopic composition. In this study, the relationship between changes in surface snow microstructure after precipitation/deposition events and water isotopes is explored using measurements of snow specific surface area (SSA). Continuous daily SSA measurements from the East Greenland Ice Core Project site (EastGRIP) situated in the accumulation zone of the Greenland Ice Sheet during the summer seasons of 2017, 2018 and 2019 are used to develop an empirical decay model to describe events of rapid decrease in SSA, driven predominantly by vapour diffusion in the pore space and atmospheric vapour exchange. The SSA decay model is described by the exponential equation SSA(t) = (SSA0 −26.8) e−0.54t + 26.8. The model performance is optimal for daily mean values of surface temperature in the range 0 °C to −25 °C and wind speed < 6 m s−1. The findings from the SSA analysis are used to explore the influence of surface snow metamorphism on altering the isotopic composition of surface snow. It is found that rapid SSA decay events correspond to decreases in d-excess over a 2-day period in 72 % of the samples. Detailed studies using Empirical Orthogonal Function (EOF) analysis revealed a coherence between the dominant mode of variance of SSA and d-excess during periods of low spatial variability of surface snow over the sampling transect, suggesting that processes driving change in SSA also influence d-excess. Our findings highlight the need for future studies to decouple the processes driving surface snow metamorphism in order to quantify the fractionation effect of individual processes on the snow isotopic composition.

Estimating Regionalized Hydrological Impacts of Climate Change Over Europe by Performance-Based Weighting of CORDEX Projections

Ensemble projections of future changes in discharge over Europe show large variation. Several methods for performance-based weighting exist that have the potential to increase the robustness of the change signal. Here we use future projections of an ensemble of three hydrological models forced with climate datasets from the Coordinated Downscaling Experiment - European Domain (EURO-CORDEX). The experiment is set-up for nine river basins spread over Europe that hold different climate and catchment characteristics. We evaluate the ensemble consistency and apply two weighting approaches; the Climate model Weighting by Independence and Performance (ClimWIP) that focuses on meteorological variables and the Reliability Ensemble Averaging (REA) in our study applied to discharge statistics per basin. For basins with a strong climate signal, in Southern and Northern Europe, the consistency in the set of projections is large. For rivers in Central Europe the differences between models become more pronounced. Both weighting approaches assign high weights to single General Circulation Models (GCMs). The ClimWIP method results in ensemble mean weighted changes that differ only slightly from the non-weighted mean. The REA method influences the weighted mean more, but the weights highly vary from basin to basin. We see that high weights obtained through past good performance can provide deviating projections for the future. It is not apparent that the GCM signal dominates the overall change signal, i.e., there is no strong intra GCM consistency. However, both weighting methods favored projections from the same GCM.

Linking the atmospheric Pacific-South American mode with oceanic variability and predictability

While Pacific climate variability is largely understood based on El Niño-Southern Oscillation (ENSO), the North Pacific focused Pacific decadal oscillation and the basin-wide interdecadal Pacific oscillation, the role of the South Pacific, including atmospheric drivers and cross-scale interactions, has received less attention. Using reanalysis data and model outputs, here we propose a paradigm for South Pacific climate variability whereby the atmospheric Pacific-South American (PSA) mode acts to excite multiscale spatiotemporal responses in the upper South Pacific Ocean. We find the second mid-troposphere PSA pattern is fundamental to stochastically generate a mid-latitude sea surface temperature quadrupole pattern that represents the optimal precursor for the predictability and evolution of both the South Pacific decadal oscillation and ENSO several seasons in advance. We find that the PSA mode is the key driver of oceanic variability in the South Pacific subtropics that generates a potentially predictable climate signal linked to the tropics.

Local-scale deposition of surface snow on the Greenland ice sheet

Ice cores from polar ice sheets and glaciers are an important climate archive. Snow layers, consecutively deposited and buried, contain climatic information from the time of their formation. However, particularly low-accumulation areas are characterised by temporally intermittent precipitation, which can be further redistributed after initial deposition, depending on the local surface features at different spatial scales. Therefore, the accumulation conditions at an ice core site influence the quantity and quality of the recorded climate signal in proxy records. This study aims to characterise the local accumulation patterns and the evolution of the snow height to describe the contribution of the snow (re-)deposition to the overall noise level in climate records from ice cores. To this end, we applied a structure-from-motion photogrammetry approach to generate near-daily elevation models of the surface snow for a 195 m2 area in the vicinity of the deep drilling site of the East Greenland Ice-core Project in northeast Greenland. Based on the snow height information we derive snow height changes on a day-to-day basis throughout our observation period from May to August 2018 and find an average snow height increase of ∼ 11 cm. The spatial and temporal data set also allows an investigation of snow deposition versus depositional modifications. We observe irregular snow deposition and erosion causing uneven snow accumulation patterns, a removal of more than 60 % of the deposited snow, and a negative relationship between the initial snow height and the amount of accumulated snow. Furthermore, the surface roughness decreased by approximately a factor of 2 throughout the spring and summer season at our study site. Finally, our study shows that structure from motion is a relatively simple method to demonstrate the potential influences of depositional processes on proxy signals in snow and ice.

Historical Forest Management Practices Influence Tree-Ring Based Climate Reconstructions

Tree-ring widths (TRW) of historical and archeological wood provide crucial proxies, frequently used for high-resolution multi-millennial paleoclimate reconstructions. Former growing conditions of the utilized trees, however, are largely unknown. Potential influences of historical forest management practices on climatic information, derived from TRW variability need to be considered but have not been assessed so far. Here, we examined the suitability of TRW series from traditionally managed oak forests (Quercus spp.) for climate reconstructions. We compared the climate signal in TRW chronologies of trees originating from high forests and coppice-with-standards (CWS) forests, a silvicultural management practice widely used in Europe for most of the common era. We expected a less distinct climate control in CWS due to management-induced growth patterns, yet an improved climate-growth relationship with TRW data from conventionally managed high forests. CWS tree rings showed considerably weaker correlations with hydroclimatic variables than non-CWS trees. The greatest potential for hydroclimate reconstructions was found for a large dataset containing both CWS and non-CWS trees, randomly collected from lumber yards, resembling the randomness in sources of historical material. Our results imply that growth patterns induced by management interventions can dampen climate signals in TRW chronologies. However, their impact can be minimized in well replicated, randomly sampled regional chronologies.

Understanding the Representativeness of Tree Rings and Their Carbon Isotopes in Characterizing the Climate Signal of Tajikistan

The juniper tree forest is a critical component of the carbon, water, and energy cycles of Tajikistan. However, to date, long-term information about tree-ring isotopes is limited in this region. Here, we developed tree-ring width (TRW) and tree-ring 13C chronologies for juniper trees (Juniperus seravschanica (Juniperus excelsa subsp.polycarpos (K. Koch) Takht.) and Juniperus turkestanica (Juniperus pseudosabina Fisch. & C. A. Mey)) and investigated their dendroclimatic signals in the northwest of the Pamir-Alay (NWPA) mountains in Tajikistan. Tree-ring ∆13C and TRW of juniper presented different sensitivities to monthly precipitation. Moreover, ∆13C in juniper showed consistently significant relationships with climatic factors in larger seasonal windows than TRW did. Dendroclimatological analysis demonstrates that precipitation has significant effects on tree growth and isotope enrichment. Late summer to early winter temperature is one limiting factor for the TRW chronologies, but previous spring, summer, and autumn temperature and precipitation from the previous July to the current May were the dominant climatic factors accounting for inter-annual variations in the ∆13C chronologies. This verified that the multi tree-ring parameters of juniper in Tajikistan are a promising tool for investigating inter-annual climate variations. Furthermore, the stable carbon isotopes of tree rings have proven to be powerful evidence of climatic signals. The moisture-sensitive tree-ring isotope provides opportunities for complex investigations of changes in atmospheric circulation patterns and timing of seasonal rainfall. Our results highlight the need for more detailed studies of tree growth responses to changing climate and tree-ring isotopes to understand source water variations (especially baseflow) of the juniper tree forest.