Inferring Past Climate from Moraine Evidence Using Glacier Modelling

<p>Glacier length fluctuations reflect changes in climate, most notably temperature and precipitation. By this reasoning, moraines, which represent former glacier extent, can be used to estimate past climate. However, estimating palaeoclimate from moraines is not a straight-forward process and involves several assumptions. For example, recent studies have suggested that interannual stochastic variability in temperature in a steady-state climate can cause a glacier to experience kilometre-scale fluctuations. Such studies cast doubt on the usefulness of moraines as climate proxy indicators. Detailed glacial geomorphological maps and moraine chronologies have improved our understanding of the spatial and temporal extent of past glacial events in New Zealand. Palaeoclimate estimates associated with these moraines have thus-far come from simple methods, such as the accumulation area ratio, with unquantifiable uncertainties. I used a numerical modelling approach to approximate the present-day glacier mass balance pattern, which includes the effects of snow avalanching on glacier mass balance. I then used the models to reconstruct palaeoclimate for Lateglacial and Holocene glacial events in New Zealand, and to better understand moraine-glacier-climate relationships. The climate reconstructions come from simulating past glacier expansions to specific terminal moraines, but I also simulated glacier fluctuations in response to a previously derived temperature reconstruction, and to interannual stochastic variability in temperature. The purpose behind each simulation was to identify the drivers of significant glacier fluctuations. The modelling results support the hypothesis that New Zealand moraine records reflect past climate, especially changes in temperature. Lateglacial climate was reconstructed to be 2-3 C lower than the present day. This temperature range agrees well with previous estimates from moraines and other climate proxy records in New Zealand. Modelled temperature estimates for the Holocene moraines are slightly colder than those derived from simpler methods, due to a non-linear relationship found between snowline lowering and glacier length. This relationship results from the specific valley shape and glacier geometry, and is likely to occur in other, similarly-shaped glacier valleys. The simulations forced by interannual stochastic variability in temperature do not show significant (>300 m) fluctuations in the glacier terminus. Such fluctuations can not explain the Holocene moraine sequence that I examined, which extends >2 km beyond the present-day glacier terminus. Stochastic temperature change could, however, in part, cause fluctuations in glacier extent during an overall glacier recession. Modelling shows that it is also unlikely that glaciers advanced to Holocene and Lateglacial moraine positions as a result of precipitation changes alone. For these reasons, temperature changes are a necessary part of explaining past glacier extents, especially during the Lateglacial, and the moraines examined here likely reflect changes in mean climate in New Zealand. The glacier modelling studies indicate that simpler methods, such as the accumulation area ratio, can be used to appropriately reconstruct past climate from glacial evidence, as long as the glacier catchment has a straight forward geometry, shallow bed slope and no tributary glaciers. Non-linear relationships between climate change and glacier length develop when valley shape is more complex, and glaciers within these systems are probably better simulated using a modelling approach. Using a numerical modelling approach, it is also possible to gain a greater understanding of glacier response time, length sensitivities, and estimates of ice extent in valleys within the model domain where geomorphic evidence is not available. In this manner, numerical models can be used as a tool for understanding past climate and glacier sensitivity, thus improving the confidence in the palaeoclimate interpretations.</p>

Inferring Past Climate from Moraine Evidence Using Glacier Modelling

<p>Glacier length fluctuations reflect changes in climate, most notably temperature and precipitation. By this reasoning, moraines, which represent former glacier extent, can be used to estimate past climate. However, estimating palaeoclimate from moraines is not a straight-forward process and involves several assumptions. For example, recent studies have suggested that interannual stochastic variability in temperature in a steady-state climate can cause a glacier to experience kilometre-scale fluctuations. Such studies cast doubt on the usefulness of moraines as climate proxy indicators. Detailed glacial geomorphological maps and moraine chronologies have improved our understanding of the spatial and temporal extent of past glacial events in New Zealand. Palaeoclimate estimates associated with these moraines have thus-far come from simple methods, such as the accumulation area ratio, with unquantifiable uncertainties. I used a numerical modelling approach to approximate the present-day glacier mass balance pattern, which includes the effects of snow avalanching on glacier mass balance. I then used the models to reconstruct palaeoclimate for Lateglacial and Holocene glacial events in New Zealand, and to better understand moraine-glacier-climate relationships. The climate reconstructions come from simulating past glacier expansions to specific terminal moraines, but I also simulated glacier fluctuations in response to a previously derived temperature reconstruction, and to interannual stochastic variability in temperature. The purpose behind each simulation was to identify the drivers of significant glacier fluctuations. The modelling results support the hypothesis that New Zealand moraine records reflect past climate, especially changes in temperature. Lateglacial climate was reconstructed to be 2-3 C lower than the present day. This temperature range agrees well with previous estimates from moraines and other climate proxy records in New Zealand. Modelled temperature estimates for the Holocene moraines are slightly colder than those derived from simpler methods, due to a non-linear relationship found between snowline lowering and glacier length. This relationship results from the specific valley shape and glacier geometry, and is likely to occur in other, similarly-shaped glacier valleys. The simulations forced by interannual stochastic variability in temperature do not show significant (>300 m) fluctuations in the glacier terminus. Such fluctuations can not explain the Holocene moraine sequence that I examined, which extends >2 km beyond the present-day glacier terminus. Stochastic temperature change could, however, in part, cause fluctuations in glacier extent during an overall glacier recession. Modelling shows that it is also unlikely that glaciers advanced to Holocene and Lateglacial moraine positions as a result of precipitation changes alone. For these reasons, temperature changes are a necessary part of explaining past glacier extents, especially during the Lateglacial, and the moraines examined here likely reflect changes in mean climate in New Zealand. The glacier modelling studies indicate that simpler methods, such as the accumulation area ratio, can be used to appropriately reconstruct past climate from glacial evidence, as long as the glacier catchment has a straight forward geometry, shallow bed slope and no tributary glaciers. Non-linear relationships between climate change and glacier length develop when valley shape is more complex, and glaciers within these systems are probably better simulated using a modelling approach. Using a numerical modelling approach, it is also possible to gain a greater understanding of glacier response time, length sensitivities, and estimates of ice extent in valleys within the model domain where geomorphic evidence is not available. In this manner, numerical models can be used as a tool for understanding past climate and glacier sensitivity, thus improving the confidence in the palaeoclimate interpretations.</p>

Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare, mainly because the climate–proxy relationships are complex and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (µXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore seasonal climate signals preserved in biochemical varves and, thus, assess the potential for annual-resolution climate reconstruction from biochemical varves. Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and µXRF-inferred elements at very high spatial resolution (60 µm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland, over the period 1966–2019 CE. We compare these data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperatures were predicted using Ti and total C (Radj2=0.55; cross-validated root mean square error (CV-RMSE) = 0.7 ∘C, 14.4 %). Windy days from March to December (mean daily wind speed > 7 m s−1) were predicted using mass accumulation rate (MAR) and Si (Radj2=0.48; CV-RMSE = 19.0 %). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate–proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual-resolution seasonal weather inference from varve biogeochemical data.

An Age Scale for the First Shallow (Sub-)Antarctic Ice Core from Young Island, Northwest Ross Sea

The climate of the sub-Antarctic is important in understanding the environmental conditions of Antarctica and the Southern Ocean. However, regional climate proxy records from this region are scarce. In this study, we present the stable water isotopes, major ion chemistry, and dust records from the first ice core from the (sub-)Antarctic Young Island. We present and discuss various dating approaches based on commonly used ice core proxies, such as stable water isotopes and seasonally deposited ions, together with site-specific characteristics such as melt layers. The dating approaches are compared with estimated precipitation rates from reanalysis data (ERA5) and volcanic cryptotephra shards likely presenting an absolute tie point from a 2001 CE eruption on neighboring Sturge Island. The resulting ice core age scale spans the period 2016 to 1995, with an uncertainty of ±2 years.

Dating historical droughts from religious ceremonies, the international pro pluvia rogation database

Climate proxy data are required for improved understanding of climate variability and change in the pre-instrumental period. We present the first international initiative to compile and share information on pro pluvia rogation ceremonies, which is a well-studied proxy of agricultural drought. Currently, the database has more than 3500 dates of celebration of rogation ceremonies, providing information for 153 locations across 11 countries spanning the period from 1333 to 1949. This product provides data for better understanding of the pre-instrumental drought variability, validating natural proxies and model simulations, and multi-proxy rainfall reconstructions, amongst other climatic exercises. The database is freely available and can be easily accessed and visualized via http://inpro.unizar.es/.

Comparison of dendroclimatic relationships using multiple tree-ring indicators (tree-ring width and δ 13 C) from Masson pine

This study addressed the effects of climate drivers on the tree-ring width (TRW) parameters (total ring width (TR), earlywood width (EW) and latewood width (LW)) and the total ring δ 13 C series of different wood components (whole wood, α-cellulose and holocelluose) from Masson pine in subtropical China. Pairwise correlation coefficients between three ring width parameters were statistically significant. EW and LW did not reveal much stronger climate sensitivity rather than TR. This indicated that the use of intra-annual ring width has little benefit in extracting more climate information. The mean δ 13 C series of the three components of the total ring had the strongest climate response to the July–September relative humidity ( r = −0.792 (whole wood), −0.758 (holocellulose) and −0.769 (α-cellulose)). There are no significant differences in the dendroclimatic relationships of the δ 13 C series of different wood components. Through both stationary temporal and spatial-statistical perspectives, the moisture drivers (summer/autumn) had a significant impact on three ring width parameters and three components of Masson pine. Overall, the radial growth and the δ 13 C series showed different responses to the same climate drivers during the same period. Moreover, the R-squared values of the strongest climate-proxy correlation coefficients were smaller than 50% for TRW. Consequently, the δ 13 C series of Masson pine may be a more representative climate proxy than TRW parameters for dendroclimatology in subtropical China.

Permafrost Biases Climate Signals in δ18Otree-ring Series from a Sub-alpine Tree Stand in Val Bever/Switzerland

During recent decades, stable oxygen isotopes derived from tree-ring cellulose (δ18OTRC) have been frequently utilised as the baseline for palaeoclimatic reconstructions. In this context, numerous studies take advantage of the high sensitivity of trees close to their ecological distribution limit (high elevation or high latitudes). However, this increases the chance that indirect climatic forces such as cold ground induced by permafrost can distort the climate-proxy relationship. In this study, a tree stand of sub-alpine larch trees (Larix decidua Mill.) located in an inner alpine dry valley (Val Bever), Switzerland, was analysed for its δ18OTRC variations during the last 180 years. A total of eight L. decidua trees were analysed on an individual base, half of which are located on verified sporadic permafrost lenses approximately 500 m below the expected lower limit of discontinuous permafrost. The derived isotope time series are strongly dependent on variations in summer temperature, precipitation and large-scale circulation patterns (geopotential height fields). The results demonstrate that trees growing outside of the permafrost distribution provide a significantly stronger and more consistent climate-proxy relationship over time than permafrost-affected tree stands. The climate sensitivity of permafrost-affected trees is analogical to the permafrost-free tree stands (positive and negative correlations with temperature and precipitation, respectively) but attenuated partly leading to a complete loss of significance. In particular, decadal summer temperature variations are well reflected in δ18OTRC from permafrost-free sites (r = 0.62, p < 0.01), while permafrost-affected sites demonstrate a full lack of this dependency (r = 0.30, p > 0.05). Since both tree stands are located just a few meters away from one another and are subject to the same climatic influences, discrepancies in the isotope time series can only be attributed to variations in the trees’ source water that constraints the climatic fingerprints on δ18OTRC. If the two individual time series are merged to one local mean chronology, the climatic sensitivity reflects an intermediate between the permafrost-free and –affected δ18OTRC time series. It can be deduced, that a significant loss of information on past climate variations arises by simply averaging both tree stands without prior knowledge of differing subsurface conditions.

Advanced Hyperspectral Analysis of Sediment Core Samples from the Chew Bahir Basin, Ethiopian Rift, in the Spectral Range from 0.25 to 17 µm: Support for Climate Proxy Interpretation

Establishing robust environmental proxies at newly investigated terrestrial sedimentary archives is a challenge, because straightforward climate reconstructions can be hampered by the complex relationship between climate parameters and sediment composition, proxy preservation or (in)sufficient sample material. We present a minimally invasive hyperspectral bidirectional reflectance analysis on discrete samples in the wavelength range from 0.25 to 17 µm on 35 lacustrine sediment core samples from the Chew Bahir Basin, southern Ethiopia for climate proxy studies. We identified and used absorption bands at 2.2 μm (Al–OH), at 2.3 μm (Mg–OH), at 1.16 μm (analcime), and at 3.98 μm (calcite) for quantitative spectral analysis. The band depth ratios at 2.3/2.2 μm in the spectra correlate with variations in the potassium content of the sediment samples, which also reflect periods of increased Al-to-Mg substitution in clay minerals during drier climatic episodes. During these episodes of drier conditions, absorption bands diagnostic of the presence of analcime and calcite support this interpretation, with analcime indicating the driest conditions. These results could be compared to qualitative analysis of other characteristic spectral properties in the spectral range between 0.25 and 17 µm. The results of the hyperspectral measurements complement previous sedimentological and geochemical analyses, allowing us in particular to resolve more finely the processes of weathering in the catchment and low-temperature authigenic processes in the sediment. This enables us to better understand environmental changes in the habitat of early humans.

Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare mainly because the climate-proxy relationships are complex, and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (μXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore (seasonal) climate signals preserved in biochemical varves and, thus, assess the potential for annual resolution climate reconstruction from biochemical varves. Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and uXRF-inferred elements at very high spatial resolution (60 μm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland over the period 1966–2019 CE. We compare this data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperature were predicted using Ti and total C (R2adj = 0.55; cross-validated root mean square error (CV-RMSE) = 0.7 °C, 14.4%). Windy days from March to December (mean daily wind speed > 7 m/s) were predicted using mass accumulation rate (MAR) and Si (R2adj = 0.48; CV-RMSE = 19.0%). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate-proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual resolution seasonal weather inference from varve biogeochemical data.

Early Eocene simulations with three different palaeogeographic conditions

&lt;p&gt;The early Eocene is a warm period with a very high atmosphere CO&lt;sub&gt;2&lt;/sub&gt; level in the Cenozoic. It &amp;#160;provides a good reference for our future climate under the Representative Concentration Pathway 8.5 scenario. Therefore, the early Eocene climate has received many attentions in &amp;#160;modeling&amp;#160;studies, for example, the Deep-Time Model Intercomparison Project (DeepMIP). However, the early Eocene palaeogeographic conditions show remarkable contrasts to the present conditions. Meanwhile, there are a few different reconstructions for the early Eocene palaeogeography, which may cause further model spreads in simulating the early Eocene warm climate. Here, we present a series of experiments carried out with the NorESM1-F, under the framework of DeepMIP. In these experiments, we consider three different palaeogeographic reconstructions for the&amp;#160;early Eocene. We also&amp;#160;compare&amp;#160;our simulations with climate proxy records, to validate which palaeogeographic reconstructions can reproduce simulations that agree better with the climate proxy records.&lt;/p&gt;