High-latitude Land Areas Research Articles

Characteristics of population exposure to climate extremes from regional to global 1.5 °C and 2.0 °C warming in CMIP6 models

The intensities and occurrences of heat extremes are projected to increase in a warmer climate, and relevant policies have been established to address different warming levels. However, how climate extremes change at regional warming levels is not well-known because changes in temperature vary over different regions. This study investigated climate extremes and population exposure to these extremes at regional and global 1.5 °C or 2.0 °C warming over 58 reference regions with 16 Coupled Model Intercomparison Project, 6th phase models. The years of reaching local 1.5 °C or 2.0 °C warming occurred earlier than the timing of global warming over certain land areas, with more than 30 years advance in northern high latitude land areas. Heat extremes are projected to increase in all reference regions under regional and global 1.5 °C or 2.0 °C warming. Moving from regional to global 1.5 °C or 2.0 °C warming, heat extremes were found to increase over most land areas, especially over mid- and high-latitude areas. Population exposure to climate extremes increased over more than half the land regions under regional to global 1.5 °C or 2.0 °C warming. Changes in population exposure to absolute heat extremes were mainly generated by changes in population over about 34 land regions, whereas changes in population exposure to percentile-based heat extremes over more than 40 land regions were mostly due to changes in climate extremes. These results provided references to establish relevant strategies at regional scale to address possible risks related to climate extremes.

Bioclimatic atlas of the terrestrial Arctic

The Arctic is the region on Earth that is warming at the fastest rate. In addition to rising means of temperature-related variables, Arctic ecosystems are affected by increasingly frequent extreme weather events causing disturbance to Arctic ecosystems. Here, we introduce a new dataset of bioclimatic indices relevant for investigating the changes of Arctic terrestrial ecosystems. The dataset, called ARCLIM, consists of several climate and event-type indices for the northern high-latitude land areas > 45°N. The indices are calculated from the hourly ERA5-Land reanalysis data for 1950–2021 in a spatial grid of 0.1 degree (~9 km) resolution. The indices are provided in three subsets: (1) the annual values during 1950–2021; (2) the average conditions for the 1991–2020 climatology; and (3) temporal trends over 1951–2021. The 72-year time series of various climate and event-type indices draws a comprehensive picture of the occurrence and recurrence of extreme weather events and climate variability of the changing Arctic bioclimate.

Newly identified climatically and environmentally significant high-latitude dust sources

Abstract. Dust particles from high latitudes have a potentially large local, regional, and global significance to climate and the environment as short-lived climate forcers, air pollutants, and nutrient sources. Identifying the locations of local dust sources and their emission, transport, and deposition processes is important for understanding the multiple impacts of high-latitude dust (HLD) on the Earth's systems. Here, we identify, describe, and quantify the source intensity (SI) values, which show the potential of soil surfaces for dust emission scaled to values 0 to 1 concerning globally best productive sources, using the Global Sand and Dust Storms Source Base Map (G-SDS-SBM). This includes 64 HLD sources in our collection for the northern (Alaska, Canada, Denmark, Greenland, Iceland, Svalbard, Sweden, and Russia) and southern (Antarctica and Patagonia) high latitudes. Activity from most of these HLD sources shows seasonal character. It is estimated that high-latitude land areas with higher (SI ≥0.5), very high (SI ≥0.7), and the highest potential (SI ≥0.9) for dust emission cover >1 670 000 km2, >560 000 km2, and >240 000 km2, respectively. In the Arctic HLD region (≥60∘ N), land area with SI ≥0.5 is 5.5 % (1 035 059 km2), area with SI ≥0.7 is 2.3 % (440 804 km2), and area with SI ≥0.9 is 1.1 % (208 701 km2). Minimum SI values in the northern HLD region are about 3 orders of magnitude smaller, indicating that the dust sources of this region greatly depend on weather conditions. Our spatial dust source distribution analysis modeling results showed evidence supporting a northern HLD belt, defined as the area north of 50∘ N, with a “transitional HLD-source area” extending at latitudes 50–58∘ N in Eurasia and 50–55∘ N in Canada and a “cold HLD-source area” including areas north of 60∘ N in Eurasia and north of 58∘ N in Canada, with currently “no dust source” area between the HLD and low-latitude dust (LLD) dust belt, except for British Columbia. Using the global atmospheric transport model SILAM, we estimated that 1.0 % of the global dust emission originated from the high-latitude regions. About 57 % of the dust deposition in snow- and ice-covered Arctic regions was from HLD sources. In the southern HLD region, soil surface conditions are favorable for dust emission during the whole year. Climate change can cause a decrease in the duration of snow cover, retreat of glaciers, and an increase in drought, heatwave intensity, and frequency, leading to the increasing frequency of topsoil conditions favorable for dust emission, which increases the probability of dust storms. Our study provides a step forward to improve the representation of HLD in models and to monitor, quantify, and assess the environmental and climate significance of HLD.

Impact of Arctic sea ice variations on winter temperature anomalies in northern hemispheric land areas

Coordinated numerical ensemble experiments with six different state-of-the-art atmosphere models have been used in order to evaluate the respective impact of the observed Arctic sea ice and sea surface temperature (SST) variations on air temperature variations in mid and high latitude land areas. Two sets of experiments have been designed; in the first set (EXP1), observed daily sea ice concentration and SST variations are used as lower boundary forcing over 1982–2014 while in the second set (EXP2) the SST variations are replaced by the daily SST climatology. The observed winter 2 m air temperature (T2m) variations are relatively well reproduced in a number of mid and high latitude land areas in EXP1, with best agreement in southwestern North America and northern Europe. Sea ice variations are important for the interannual T2m variations in northern Europe but have limited impact on all other mid and high latitude land regions. In particular, sea ice variations do not contribute to the observed opposite variations in the Arctic and mid latitude in our model experiments. The spread across ensemble members is large and many ensemble members are required to reproduce the observed T2m variations over northern Europe in our models. The amplitude of T2m anomalies in the coldest observed winters over northern Europe is not reproduced by our multi-model ensemble means. However, the sea ice conditions in these respective winters and mainly the thermodynamic response to the ice anomalies lead to an enhanced likelihood for occurrence of colder than normal winters and extremely cold winters. Still, the main reason for the observed extreme cold winters is internal atmospheric dynamics. The coldest simulated northern European winters in EXP1 and EXP2 between 1982 and 2014 show the same large scale T2m and atmospheric circulation anomaly patterns as the observed coldest winters, indicating that the models are well able to reproduce the processes, which cause these cold anomalies. The results are robust across all six models used in this study.

Abrupt high-latitude climate events and decoupled seasonal trends during the Eemian

The Eemian (the Last Interglacial; ca. 129–116 thousand years ago) presents a testbed for assessing environmental responses and climate feedbacks under warmer-than-present boundary conditions. However, climate syntheses for the Eemian remain hampered by lack of data from the high-latitude land areas, masking the climate response and feedbacks in the Arctic. Here we present a high-resolution (sub-centennial) record of Eemian palaeoclimate from northern Finland, with multi-model reconstructions for July and January air temperature. In contrast with the mid-latitudes of Europe, our data show decoupled seasonal trends with falling July and rising January temperatures over the Eemian, due to orbital and oceanic forcings. This leads to an oceanic Late-Eemian climate, consistent with an earlier hypothesis of glacial inception in Europe. The interglacial is further intersected by two strong cooling and drying events. These abrupt events parallel shifts in marine proxy data, linked to disturbances in the North Atlantic oceanic circulation regime.

Surface-Atmosphere Moisture Interactions in the Frozen Ground Regions of Eurasia.

Climate models simulate an intensifying Arctic hydrologic cycle in response to climatic warming, however the role of surface-atmosphere interactions from degrading frozen ground is unclear in these projections. Using Modern-Era Retrospective Analysis for Research and Applications (MERRA) data in high-latitude Eurasia, we examine long-term variability in surface-atmosphere coupling as represented by the statistical relationship between surface evaporative fraction (EF) and afternoon precipitation. Changes in EF, precipitation, and their statistical association are then related to underlying permafrost type and snow cover. Results indicate significant positive trends in July EF in the Central Siberian Plateau, corresponding to significant increases in afternoon precipitation. The positive trends are only significant over continuous permafrost, with non-significant or negative EF and precipitation trends over isolated, sporadic, and discontinuous permafrost areas. Concurrently, increasing EF and subsequent precipitation are found to coincide with significant trends in May and June snowmelt, which potentially provides the moisture source for the observed enhanced latent heating and moisture recycling in the region. As climate change causes continuous permafrost to transition to discontinuous, discontinuous to sporadic, sporadic to isolated, and isolated permafrost disappears, this will also alter patterns of atmospheric convection, moisture recycling, and hence the hydrologic cycle in high-latitude land areas.

Human Influences on Changes in the Temperature Seasonality in Mid- to High-Latitude Land Areas

Abstract The annual cycle is the largest variability for many climate variables outside the tropics. Whether human activities have affected the annual cycle at the regional scale is unclear. In this study, long-term changes in the amplitude of surface air temperature annual cycle in the observations are compared with those simulated by the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Different spatial domains ranging from hemispheric to subcontinental scales in mid- to high-latitude land areas for the period 1950–2005 are considered. Both the optimal fingerprinting and a nonoptimal detection and attribution technique are used. The results show that the space–time pattern of model-simulated responses to the combined effect of anthropogenic and natural forcings is consistent with the observed changes. In particular, models capture not only the decrease in the temperature seasonality in the northern high latitudes and East Asia, but also the increase in the Mediterranean region. A human influence on the weakening in the temperature seasonality in the Northern Hemisphere is detected, particularly in the high latitudes (50°–70°N) where the influence of the anthropogenic forcing can be separated from that of the natural forcing.

Human-Induced Arctic Moistening

The Arctic and northern subpolar regions are critical for climate change. Ice-albedo feedback amplifies warming in the Arctic, and fluctuations of regional fresh water inflow to the Arctic Ocean modulate the deep ocean circulation and thus exert a strong global influence. By comparing observations to simulations from 22 coupled climate models, we find influence from anthropogenic greenhouse gases and sulfate aerosols in the space-time pattern of precipitation change over high-latitude land areas north of 55 degrees N during the second half of the 20th century. The human-induced Arctic moistening is consistent with observed increases in Arctic river discharge and freshening of Arctic water masses. This result provides new evidence that human activity has contributed to Arctic hydrological change.

Clouds modulate terrestrial carbon uptake in a midlatitude hardwood forest

[1] Thirteen years of turbulent exchange and radiation measurements in a midlatitude hardwood forest show that clouds enhance radiation use efficiency of carbon uptake (RUE), and that maximum carbon uptake occurs under moderate cloud cover. We find that both cyclic and secular variability of a simple observable metric of cloudiness (transmittance index) is the best statistical predictor of the interannual variability of both net ecosystem production (NEP) and gross ecosystem production (GEP) seen in our dataset. In contrast other factors analyzed show much weaker relationships with the terrestrial carbon uptake. This suggests that clouds play a pivotal role in driving the interannual variability of terrestrial carbon uptake by this forest and are an important mechanism of carbon cycle/ climate interaction. [2] The interannual variability in the growth rate of atmospheric CO2 is modulated significantly by terrestrial ecosystem processes [Houghton, 2000]. The interaction of climate with regional characteristics of ecosystems imposes complex controlling factors on carbon uptake in different vegetation and climate regimes around the world [Churkina and Running, 1998; Nemani et al., 2003; Barford et al., 2001]. Recent studies suggest that climate change, along with alteration of CO2 fertilization, nitrogen deposition and land-use characteristics, alters the global terrestrial ecosystem through several controlling factors in terrestrial carbon uptake (e.g., temperature [Braswell et al., 1997; Lucht et al., 2000], precipitation [Nemani et al., 2002], and radiation [Nemani et al., 2003; Gu et al., 2003]). However, the presence of clouds can both cause, and be the consequence of, changes in these controls, and subsequent impacts on stomatal dynamics through changes in leaf temperature and leaf-to-air water vapor pressure deficit (WVPD) [Min, 2005]. [3] Total cloud cover has increased about 2% over many midto high-latitude land areas since the beginning of the 20th Century [Intergovernmental Panel on Climate Change (IPCC), 2001]. The increase in total cloud amount, combined with secondary damping effects through soil moisture and precipitation, affects surface temperatures and is negatively correlated with diurnal temperature ranges [Dai et al., 1997]. Clouds also strongly affect the geographic patterns of diurnal temperature range [Dai et al., 1999]. Moreover, changes in precipitation in midand high-latitudes over land have a strong correlation with long-term changes in total cloud amount [IPCC, 2001]. Clouds also modulate solar radiation and photosynthetically-active radiation (PAR) to favour photosynthesis by changing the spectral distribution (light ‘‘spectral quality’’) and diffuse fraction [Min, 2005] and alter stomatal dynamics in fluctuating light environments [Fitzjarrald et al., 1995]. Observational evidence shows that carbon uptake by plants is enhanced on days when the diffuse component of PAR is augmented by clouds or aerosols [Gu et al., 2003; Min, 2005; IPCC, 2001; Hollinger et al., 1994; Price and Black, 1990; Fan et al., 1995; Gu et al., 1999; Freedman et al., 2001; Gu et al., 2002; Niyogi et al., 2004]. [4] Clouds are linked to key factors of climate variability, but their role in the interannual variation of terrestrial CO2 exchange on ecosystem or larger scales has received relatively little attention. Here we examine interannual variability of temperature, precipitation, and cloud distribution and their effects on carbon uptake by analyzing long term turbulent CO2 exchange and radiation measurements from 1992 to 2004 at a northern hardwood forest (Harvard Forest, 42.5N, 72.2W) [Wofsy et al., 1993] (see http://harvardforest. fas.harvard.edu/). The net ecosystem production (NEP) was computed based on the eddy correlation measurements of carbon uptake [Wofsy et al., 1993]. The gross ecosystem production (GEP) was calculated by subtracting respiration (RESP) from NEP, where respiration was measured directly at night and extrapolated for daytime on the basis of daynight changes in soil temperature [Barford et al., 2001; Goulden et al., 1996; Wofsy et al., 1993]. [5] We use the atmospheric transmittance index (TI) as a measure of cloudiness and aerosol loading, as derived from measured surface shortwave radiation after removing dependences of solar zenith angle and solar distance. Radiation impacts due to changes in aerosol and water vapor are relatively smaller than those due to changes in cloud fraction and optical properties. Thus, TI can be viewed as a measure of clouds with the combined effect of both cloud fraction and cloud optical depth, directly linking to the surface cloud forcing defined by Betts and Viterbo [2005]. A smaller TI is produced by a larger cloud/ aerosol optical depth or a greater cloud cover or a combined effect of cloud cover and cloud optical depth in partly cloudy conditions (see auxiliary material).

The Diurnal Cycle and Its Depiction in the Community Climate System Model

To evaluate the performance of version 2 of the Community Climate System Model (CCSM2) in simulating the diurnal cycle and to diagnose the deficiencies in underlying model physics, 10 years of 3-hourly data from a CCSM2 control run are analyzed for global and large-scale features of diurnal variations in surface air temperature, surface pressure, upper-air winds, cloud amount, and precipitation. The model-simulated diurnal variations are compared with available observations, most of which were derived from 3-hourly synoptic reports and some new results are reported for surface air temperatures. The CCSM2 reproduces most of the large-scale tidal variations in surface pressure and upper-air winds, although it overestimates the diurnal pressure tide by 20%–50% over low-latitude land and underestimates it over most oceans, the Rockies, and other midlatitude land areas. The CCSM2 captures the diurnal amplitude (1°–6°C) and phase [peak at 1400–1600 local solar time (LST)] of surface air temperature over land, but over ocean the amplitude is too small (≤0.2°C). The CCSM2 overestimates the mean total cloud amount by 10%–20% of the sky from ∼15°S to 15°N during both December– January–February (DJF) and June–July–August (JJA) and over northern mid- and high-latitude land areas in DJF, whereas it underestimates the cloud amount by 10%–30% in the subtropics and parts of the midlatitudes. Over the marine stratocumulus regions west to the continents, the diagnostic cloud scheme in the CCSM2 underestimates the mean stratocumulus amount by 10%–30% and does not simulate the observed large diurnal variations (∼3%–10%) in the marine stratocumulus clouds even when driven by observational data. In the CCSM2, warm-season daytime moist convection over land starts prematurely around 0800 LST, about 4 hours too early compared with observations, and plateaus from 1100 to 1800 LST, in contrast to a sharp peak around 1600–1700 LST in observations. The premature initiation of convection prevents convective available potential energy (CAPE) from accumulating in the morning and early afternoon and intense convection from occurring in the mid to late afternoon. As a result of the extended duration of daytime convection over land, the CCSM2 rains too frequently at reduced intensity despite the fairly realistic patterns of rainy days with precipitation >1 mm day−1. Furthermore, the convective versus nonconvective precipitation ratio is too high in the model as deep convection removes atmospheric moisture prematurely. The simulated diurnal cycle of precipitation is too weak over the oceans, especially for convective precipitation. These results suggest that substantial improvements are desirable in the CCSM2 in simulating cloud amount, initiation of warm-season deep convection over land, and in the diurnal cycle in sea surface temperatures.

Climates of the Twentieth and Twenty-First Centuries Simulated by the NCAR Climate System Model

The Climate System Model, a coupled global climate model without “flux adjustments” recently developed at the National Center for Atmospheric Research, was used to simulate the twentieth-century climate using historical greenhouse gas and sulfate aerosol forcing. This simulation was extended through the twenty-first century under two newly developed scenarios, a business-as-usual case (ACACIA-BAU, CO2 ≈ 710 ppmv in 2100) and a CO2 stabilization case (STA550, CO2 ≈ 540 ppmv in 2100). Here we compare the simulated and observed twentieth-century climate, and then describe the simulated climates for the twenty-first century. The model simulates the spatial and temporal variations of the twentieth-century climate reasonably well. These include the rapid rise in global and zonal mean surface temperatures since the late 1970s, the precipitation increases over northern mid- and high-latitude land areas, ENSO-induced precipitation anomalies, and Pole–midlatitude oscillations (such as the North Atlantic oscillation) in sea level pressure fields. The model has a cold bias (2°–6°C) in surface air temperature over land, overestimates of cloudiness (by 10%–30%) over land, and underestimates of marine stratus clouds to the west of North and South America and Africa. The projected global surface warming from the 1990s to the 2090s is ∼1.9°C under the BAU scenario and ∼1.5°C under the STA550 scenario. In both cases, the midstratosphere cools due to the increase in CO2, whereas the lower stratosphere warms in response to recovery of the ozone layer. As in other coupled models, the surface warming is largest at winter high latitudes (≥5.0°C from the 1990s to the 2090s) and smallest (∼1.0°C) over the southern oceans, and is larger over land areas than ocean areas. Globally averaged precipitation increases by ∼3.5% (3.0%) from the 1990s to the 2090s in the BAU (STA550) case. In the BAU case, large precipitation increases (up to 50%) occur over northern mid- and high latitudes and over India and the Arabian Peninsula. Marked differences occur between the BAU and STA550 regional precipitation changes resulting from interdecadal variability. Surface evaporation increases at all latitudes except for 60°–90°S. Water vapor from increased tropical evaporation is transported into mid- and high latitudes and returned to the surface through increased precipitation there. Changes in soil moisture content are small (within ±3%). Total cloud cover changes little, although there is an upward shift of midlevel clouds. Surface diurnal temperature range decreases by about 0.2°–0.5°C over most land areas. The 2–8-day synoptic storm activity decreases (by up to 10%) at low latitudes and over midlatitude oceans, but increases over Eurasia and Canada. The cores of subtropical jets move slightly up- and equatorward. Associated with reduced latitudinal temperature gradients over mid- and high latitudes, the wintertime Ferrel cell weakens (by 10%–15%). The Hadley circulation also weakens (by ∼10%), partly due to the upward shift of cloudiness that produces enhanced warming in the upper troposphere.

Vegetation-induced warming of high-latitude regions during the Late Cretaceous period

Modelling studies of pre-Quaternary (>2 million years ago) climate implicate atmospheric carbon dioxide concentrations1, land elevation2 and land–sea distribution3–5 as important factors influencing global climate change over geological timescales. But during times of global warmth, such as the Cretaceous period and Eocene epoch, there are large discrepancies between model simulations of high-latitude and continental-interior temperatures and those indicated by palaeotemperature records6,7. Here we use a global climate model for the latest Cretaceous (66 million years ago) to examine the role played by high- and middle-latitude forests in surface temperature regulation. In our simulations, this forest vegetation warms the global climate by 2.2 °C. The low-albedo deciduous forests cause high-latitude land areas to warm, which then transfer more heat to adjacent oceans, thus delaying sea-ice formation and increasing winter temperatures over coastal land. Overall, the inclusion of some of the physical and physiological climate feedback effects of high-latitude forest vegetation in our simulations reduces the existing discrepancies between observed and modelled climates of the latest Cretaceous, suggesting that these forests may have made an important contribution to climate regulation during periods of global warmth.

Geological Assessment of the Greenhouse Effect

Geologic studies provide a valuable perspective on the importance of greenhouse forcing for climate change. On both Pleistocene and tectonic time scales, changes in climate are positively correlated with greenhouse gas variations. However, the sensitivity of the system to greenhouse gas changes cannot yet be constrained by paleoclimate data below its present large range. Geologic records do not support one of the major predictions of greenhouse models—namely, that tropical sea surface temperatures will increase. Geologic data also suggest that winter cooling in high-latitude land areas is less than predicted by models. As the above-mentioned predictions appear to be systemic features of the present generation of climate models, some significant changes in model design may be required to reconcile models and geologic data. However, full acceptance of this conclusion requires more measurements and more systematic compilations of existing geologic data. Since progress in data collection in this area has been quite slow, uncertainties associated with these conclusions may persist for some time.