Moisture transport in observations and reanalyses as a proxy for snow accumulation in East Antarctica

Atmospheric moisture convergence on ice sheets provides an estimate of snow accumulation, which is critical to quantifying sea-level changes. In the case of East Antarctica, we computed moisture transport from 1980 to 2016 in five reanalyses and in radiosonde observations. Moisture convergence in reanalyses is more consistent than net precipitation but still ranges from 72 to 96&thinsp;mm&thinsp;yr−1 in the four most recent reanalyses, ERA-Interim, NCEP CFSR, JRA 55 and MERRA 2. The representation of long-term variability in reanalyses is also inconsistent, which justified resorting to observations. Moisture fluxes are measured on a daily basis via radiosondes launched from a network of stations surrounding East Antarctica. Observations agree with reanalyses on the major role of extreme advection events and transient eddy fluxes. Although assimilated, the observations reveal processes that reanalyses cannot model, some due to a lack of horizontal and vertical resolution, especially the oldest, NCEP DOE R2. Additionally, the observational time series are not affected by new satellite data unlike the reanalyses. We formed pan-continental estimates of convergence by aggregating anomalies from all available stations. We found statistically significant trends neither in moisture convergence nor in precipitable water.</p

Water Cycle Changes

This chapter assesses multiple lines of evidence to evaluate past, present and future changes in the global water cycle. It complements material in Chapters 2, 3 and 4 on observed and projected changes in the water cycle, and Chapters 10 and 11 on regional climate change and extreme events. The assessment includes the physical basis for water cycle changes, observed changes in the water cycle and attribution of their causes, future projections and related key uncertainties, and the potential for abrupt change. Paleoclimate evidence, observations, reanalyses and global and regional model simulations are considered. The assessment shows widespread, nonuniform human-caused alterations of the water cycle, which have been obscured by a competition between different drivers across the 20th century and that will be increasingly dominated by greenhouse gas forcing at the global scale

Summer weather becomes more persistent in a 2 °C world

Heat and rainfall extremes have intensified over the past few decades and this trend is projected to continue with future global warming1–3. A long persistence of extreme events often leads to societal impacts with warm-and-dry conditions severely affecting agriculture and consecutive days of heavy rainfall leading to flooding. Here we report systematic increases in the persistence of boreal summer weather in a multi-model analysis of a world 2 °C above pre-industrial compared to present-day climate. Averaged over the Northern Hemisphere mid-latitude land area, the probability of warm periods lasting longer than two weeks is projected to increase by 4% (2–6% full uncertainty range) after removing seasonal-mean warming. Compound dry–warm persistence increases at a similar magnitude on average but regionally up to 20% (11–42%) in eastern North America. The probability of at least seven consecutive days of strong precipitation increases by 26% (15–37%) for the mid-latitudes. We present evidence that weakening storm track activity contributes to the projected increase in warm and dry persistence. These changes in persistence are largely avoided when warming is limited to 1.5 °C. In conjunction with the projected intensification of heat and rainfall extremes, an increase in persistence can substantially worsen the effects of future weather extremes

Prolonged Siberian heat of 2020 almost impossible without human influence

Over the first half of 2020, Siberia experienced the warmest period from January to June since records began and on the 20th of June the weather station at Verkhoyansk reported 38 °C, the highest daily maximum temperature recorded north of the Arctic Circle. We present a multi-model, multi-method analysis on how anthropogenic climate change affected the probability of these events occurring using both observational datasets and a large collection of climate models, including state-of-the-art higher-resolution simulations designed for attribution and many from the latest generation of coupled ocean-atmosphere models, CMIP6. Conscious that the impacts of heatwaves can span large differences in spatial and temporal scales, we focus on two measures of the extreme Siberian heat of 2020: January to June mean temperatures over a large Siberian region and maximum daily temperatures in the vicinity of the town of Verkhoyansk. We show that human-induced climate change has dramatically increased the probability of occurrence and magnitude of extremes in both of these (with lower confidence for the probability for Verkhoyansk) and that without human influence the temperatures widely experienced in Siberia in the first half of 2020 would have been practically impossible

On tail trend detection: modeling relative risk

The climate change dispute is about changes over time of environmental characteristics (such as rainfall). Some people say that a possible change is not so much in the mean but rather in the extreme phenomena (that is, the average rainfall may not change much but heavy storms may become more or less frequent). The paper studies changes over time in the probability that some high threshold is exceeded. The model is such that the threshold does not need to be specified, the results hold for any high threshold. For simplicity a certain linear trend is studied depending on one real parameter. Estimation and testing procedures (is there a trend?) are developed. Simulation results are presented. The method is applied to trends in heavy rainfall at 18 gauging stations across Germany and The Netherlands. A tentative conclusion is that the trend seems to depend on whether or not a station is close to the sea.Comment: 38 page

Influence of the ocean surface temperature and sea ice concentration on regional climate changes in Eurasia in recent decades

Numerical experiments with the ECHAM5 atmospheric general circulation model have been performed in order to simulate the influence of changes in the ocean surface temperature (OST) and sea ice concentration (SIC) on climate characteristics in regions of Eurasia. The sensitivity of winter and summer climates to OST and SIC variations in 1998-2006 has been investigated and compared to those in 1968-1976. These two intervals correspond to the maximum and minimum of the Atlantic Long-Period Oscillation (ALO) index. Apart from the experiments on changes in the OST and SIC global fields, the experiments on OST anomalies only in the North Atlantic and SIC anomalies in the Arctic for the specified periods have been analyzed. It is established that temperature variations in Western Europe are explained by OST and SIC variations fairly well, whereas the warmings in Eastern Europe and Western Siberia, according to model experiments, are substantially (by a factor of 2-3) smaller than according to observational data. Winter changes in the temperature regime in continental regions are controlled mainly by atmospheric circulation anomalies. The model, on the whole, reproduces the empirical structure of changes in the winter field of surface pressure, in particular, the pressure decrease in the Caspian region; however, it substantially (approximately by three times) underestimates the range of changes. Summer temperature variations in the model are characterized by a higher statistical significance than winter ones. The analysis of the sensitivity of the climate in Western Europe to SIC variations alone in the Arctic is an important result of the experiments performed. It is established that the SIC decrease and a strong warming over the Barents Sea in the winter period leads to a cooling over vast regions of the northern part of Eurasia and increases the probability of anomalously cold January months by two times and more (for regions in Western Siberia). This effect is caused by the formation of the increased-pressure region with a center over the southern boundary of the Barents Sea during the SIC decrease and an anomalous advection of cold air masses from the northeast. This result indicates that, to estimate the ALO actions (as well as other long-scale climatic variability modes) on the climate of Eurasia, it is basically important to take into account (or correctly reproduce) Arctic sea ice changes in experiments with climatic models

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the twenty-first century

© 2017, The Author(s). During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Spring snow albedo feedback over northern Eurasia: Comparing in situ measurements with reanalysis products

This study uses daily observations and modern reanalyses in order to evaluate reanalysis products over northern Eurasia regarding the spring snow albedo feedback (SAF) during the period from 2000 to 2013. We used the state-of-the-art reanalyses from ERA-Interim/Land and the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) as well as an experimental set-up of ERA-Interim/Land with prescribed short grass as land cover to enhance the comparability with the station data while underlining the caveats of comparing in situ observations with gridded data. Snow depth statistics derived from daily station data are well reproduced in all three reanalyses. However day-to-day albedo variability is notably higher at the stations than for any reanalysis product. The ERA-Interim grass set-up shows improved performance when representing albedo variability and generates comparable estimates for the snow albedo in spring. We find that modern reanalyses show a physically consistent representation of SAF, with realistic spatial patterns and area-averaged sensitivity estimates. However, station-based SAF values are significantly higher than in the reanalyses, which is mostly driven by the stronger contrast between snow and snow-free albedo. Switching to grass-only vegetation in ERA-Interim/Land increases the SAF values up to the level of station-based estimates. We found no significant trend in the examined 14-year time series of SAF, but interannual changes of about 0.5 % K−1 in both station-based and reanalysis estimates were derived. This interannual variability is primarily dominated by the variability in the snowmelt sensitivity, which is correctly captured in reanalysis products. Although modern reanalyses perform well for snow variables, efforts should be made to improve the representation of dynamic albedo changes