Brief communication: An ice surface melt scheme including the diurnal cycle of solar radiation

We propose a surface melt scheme for glaciated land surfaces, which only requires monthly mean short-wave radiation and temperature as inputs, yet implicitly accounts for the diurnal cycle of short-wave radiation. The scheme is deduced from the energy balance of a daily melt period, which is defined by a minimum solar elevation angle. The scheme yields a better spatial representation of melting than common empirical schemes when applied to the Greenland Ice Sheet, using a 1948–2016 regional climate and snowpack simulation as a reference. The scheme is physically constrained and can be adapted to other regions or time periods.</p

Higher sea surface temperature in the Indian Ocean during the Last Interglacial weakened the South Asian monsoon

Addressing and anticipating future South Asian monsoon changes under continuing global warming is of critical importance for the food security and socioeconomic well-being of one-quarter of the world’s population. However, climate model projections show discrepancies in future monsoon variability in South Asian monsoon domains, largely due to our still limited understanding of the monsoon response to warm climate change scenarios. Particularly, climate models are largely based on the assumption that higher solar insolation causes higher rainfall during similar warm climatic regimes, but this has not been verified by proxy data for different interglacial periods. Here, we compare Indian summer monsoon (ISM) variability during the Last Interglacial and Holocene using a sedimentary leaf wax δD and δ13C record from the northern Bay of Bengal, representing the Ganges–Brahmaputra–Meghna (G-B-M) river catchment. In combination with a seawater salinity record, our results show that ISM intensity broadly follows summer insolation on orbital scales, but ISM intensity during the Last Interglacial was lower than during the Holocene despite higher summer insolation and greenhouse gas concentrations. We argue that sustained warmer sea surface temperature in the equatorial and tropical Indian Ocean during the Last Interglacial increased convective rainfall above the ocean but dampened ISM intensity on land. Our study demonstrates that besides solar insolation, internal climatic feedbacks also play an important role for South Asian monsoon variability during warm climate states. This work can help to improve future climate model projections and highlights the importance of understanding controls of monsoonal rainfall under interglacial boundary conditions.Geological Setting and Proxy Records Results - Variations of n-Alkane δD and δ13C Values. - δDivc Values in Sediment Core 17286-1 Reflect ISM Intensity and Rainfall Amount. - ISM Rainfall Shifts in South Asia. - Vegetation Changes in South Asia. Discussion - Climatic Controls on ISM Intensity at Millennial to Orbital Time Scales. - Internal Climatic Feedback of South Asian Monsoon Variability during the Last Interglacial and the Holocene - Mechanisms Controlling Vegetation Variability in South Asia. - Perspectives. Method

Last interglacial temperature evolution – a model inter-comparison

Abstract. There is a growing number of proxy-based reconstructions detailing the climatic changes during the Last Interglacial period. This period is of special interest because large parts of the globe were characterized by a warmer-than-present-day climate, making this period an interesting test bed for climate models in the light of projected global warming. However, mainly because synchronizing the different records is difficult, there is no consensus on a global picture of Last Interglacial temperature changes. Here we present the first model inter-comparison of transient simulations covering the Last Interglacial period. By comparing the different simulations we aim at investigating the robustness of the simulated surface air temperature evolution. The model inter-comparison shows a robust Northern Hemisphere July temperature evolution characterized by a maximum between 130–122 ka BP with temperatures 0.4 to 6.8 K above pre-industrial values. This temperature evolution is in line with the changes in June insolation and greenhouse-gas concentrations. For the evolution of July temperatures in the Southern Hemisphere, the picture emerging from the inter-comparison is less clear. However, it does show that including greenhouse-gas concentration changes is critical. The simulations that include this forcing show an early, 128 ka BP July temperature anomaly maximum of 0.5 to 2.6 K. The robustness of simulated January temperatures is large in the Southern Hemisphere and the mid-latitudes of the Northern Hemisphere. In these latitudes maximum January temperature anomalies of respectively −2.5 to 2 K and 0 to 2 K are simulated for the period after 118 ka BP. The inter-comparison is inconclusive on the evolution of January temperatures in the high-latitudes of the Northern Hemisphere. Further investigation of regional anomalous patterns and inter-model differences indicate that in specific regions, feedbacks within the climate system are important for the simulated temperature evolution. Firstly in the Arctic region, changes in the summer sea-ice cover control the evolution of Last Interglacial winter temperatures. Secondly, for the Atlantic region, the Southern Ocean and the North Pacific, possible changes in the characteristics of the Atlantic meridional overturning circulation are critical. The third important feedback, having an impact on the temperature evolution of the Northern Hemisphere, is shown to be the presence of remnant continental ice from the preceding glacial period. Another important feedback are changes in the monsoon regime which controls the evolution of temperatures over parts of Africa and India. Finally, the simulations reveal an important land-sea contrast, with temperature changes over the oceans lagging continental temperatures by up to several thousand years. The aforementioned feedback mechanisms tend to be highly model-dependent, indicating that specific proxy-data is needed to constrain future climate simulations and to further enhance our understanding of the evolution of the climate during the Last Interglacial period

Climate and CO2 effects on the vegetation of southern tropical Africa over the last 37,000 years

The savanna vegetation of southern tropical Africa is characterized by co-dominance of C-4 grasslands and C-3 woodlands. Long-term variations in the tropical savanna vegetation in arid and semi-arid climates are commonly considered to be primarily sensitive to precipitation and atmospheric CO2 concentrations. The sensitivity of tropical vegetation to temperature, however, is often considered as secondary or negligible, particularly in paleostudies due to difficulties of reconstructing terrestrial temperature in the tropics. In this study, we use the terrestrial vegetation model BIOME4, which was forced by climate simulations from the Kiel Climate Model (KCM) for the Holocene and by climate reconstructions for the most recent glacial period to understand reconstructed vegetation changes in southern tropical Africa of the past 37,000 yr. We focus on these two periods because vegetation reconstructions from a marine sediment core near the Zambezi River mouth cannot be explained by precipitation changes and changes of atmospheric CO2 alone. For the Holocene, we force BIOME4 simulations with reconstructed atmospheric CO2 concentrations, and spatial and seasonal climate patterns from the early- and mid-Holocene (9.5 and 6 ka BP) simulations with the KCM. For the glacial period, we analyze idealized experiments based upon reconstructed temperature, precipitation and CO2 at 31, 28 and 21 ka BP. Our study shows that both Holocene and glacial simulations of vegetation cover exhibit good agreement with reconstructed C-4:C-3 ratios when temperature changes are taken into account. While both precipitation and temperature control the C-4:C-3 ratio during the Holocene atmospheric CO2 and temperature variations are major factors controlling vegetation changes during the glacial period. In our simulations, variations in temperature along with precipitation and atmospheric CO2 reconcile the evolution of vegetation observed in the Zambezi catchment during the last 37,000 yr. In consequence, the effect of temperature variations on tropical savanna vegetation should be taken into account with respect to modeling past or future climates. (C) 2014 Elsevier B.V. All rights reserved

A multi-model assessment of last interglacial temperatures

The last interglaciation (~130 to 116 ka) is a time period with a strong astronomically induced seasonal forcing of insolation compared to the present. Proxy records indicate a significantly different climate to that of the modern, in particular Arctic summer warming and higher eustatic sea level. Because the forcings are relatively well constrained, it provides an opportunity to test numerical models which are used for future climate prediction. In this paper we compile a set of climate model simulations of the early last interglaciation (130 to 125 ka), encompassing a range of model complexities. We compare the simulations to each other and to a recently published compilation of last interglacial temperature estimates. We show that the annual mean response of the models is rather small, with no clear signal in many regions. However, the seasonal response is more robust, and there is significant agreement amongst models as to the regions of warming vs cooling. However, the quantitative agreement of the model simulations with data is poor, with the models in general underestimating the magnitude of response seen in the proxies. Taking possible seasonal biases in the proxies into account improves the agreement, but only marginally. However, a lack of uncertainty estimates in the data does not allow us to draw firm conclusions. Instead, this paper points to several ways in which both modelling and data could be improved, to allow a more robust model–data comparison

Temperature trends during the Present and Last Interglacial periods - a multi-model-data comparison

Though primarily driven by insolation changes associated with well-known variations in Earth's astronomical parameters, the response of the climate system during interglacials includes a diversity of feedbacks involving the atmosphere, ocean, sea ice, vegetation and land ice. A thorough multimodel- data comparison is essential to assess the ability of climate models to resolve interglacial temperature trends and to help in understanding the recorded climatic signal and the underlying climate dynamics. We present the first multi-model-data comparison of transient millennial-scale temperature changes through two intervals of the Present Interglacial (PIG; 8-1.2 ka) and the Last Interglacial (LIG; 123-116.2 ka) periods. We include temperature trends simulated by 9 different climate models, alkenone-based temperature reconstructions from 117 globally distributed locations (about 45% of them within the LIG) and 12 ice-core-based temperature trends from Greenland and Antarctica (50% of them within the LIG). The definitions of these specific interglacial intervals enable a consistent inter-comparison of the two intervals because both are characterised by minor changes in atmospheric greenhouse gas concentrations and more importantly by insolation trends that show clear similarities. Our analysis shows that in general the reconstructed PIG and LIG Northern Hemisphere mid-to-high latitude cooling compares well with multi-model, mean-temperature trends for the warmest months and that these cooling trends reflect a linear response to the warmest-month insolation decrease over the interglacial intervals. The most notable exception is the strong LIG cooling trend reconstructed from Greenland ice cores that is not simulated by any of the models. A striking model-data mismatch is found for both the PIG and the LIG over large parts of the mid-to-high latitudes of the Southern Hemisphere where the data depicts negative temperature trends that are not in agreement with near zero trends in the simulations. In this area, the positive local summer insolation trend is counteracted in climate models by an enhancement of the Southern Ocean summer sea-ice cover and/or an increase in Southern Ocean upwelling. If the general picture emerging from reconstructions is realistic, then the model-data mismatch in mid and high Southern Hemisphere latitudes implies that none of the models is able to resolve the correct balance of these feedbacks, or, alternatively, that interglacial Southern Hemisphere temperature trends are driven by mechanisms which are not included in the transient simulations, such as changes in the Antarctic ice sheet or meltwater-induced changes in the overturning circulation