Snow Feedbacks Research Articles

Prediction of net primary productivity in the middle-to-high latitudes of Eurasia based on snow and soil temperature

Net primary productivity (NPP) is the net accumulation of organic matter by vegetation through photosynthesis and serves as a key indicator for exploring vegetation responses to climate change. Considering the remote and local impacts of soil heat capacities on vegetation growth through pathways of atmospheric circulation and land–atmosphere interaction, this paper develops a statistical prediction model for NPP from April to June (AMJ) across the middle-to-high latitudes of Eurasia. The model introduces two physically meaningful predictors: the snow water equivalent (SWE) from February to March (FM) over central Europe and the FM local soil temperature (ST). The positive phase of FM SWE triggers anomalous eastward-propagating Rossby waves, leading to an anomalous low-pressure system and cooling in the middle-to-high latitudes of Eurasia. This effect persists into spring through snow feedback to the atmosphere and affects subsequent NPP changes. The ST is closely related to the AMJ temperature and precipitation. With positive ST anomalies, the AMJ temperature and precipitation exhibit an east–west dipole anomaly distribution in this region. The single-factor prediction scheme using ST as the predictor is much better than using SWE as the predictor. Independent validation results from 2009 to 2014 demonstrate that the ST scheme alone has good predictive performance for the spatial distribution and interannual variability of NPP. The predictive skills of the multi-factor prediction schemes can be improved by about 13 % if the ST predictor is included. The findings confirm that local ST is a predictor that must be included for NPP prediction.摘要净初级生产力 (NPP) 是植被通过光合作用积累机物质的净效益, 是探索植被对气候变化响应的关键指标. 考虑到陆面热力异常通过陆气相互作用和大尺度环流对植被生长的影响, 本文研制了欧亚中高纬地区4–6月NPP预测模型. 该模型引入了两个具有明确物理意义的预测因子: 欧洲中部2–3月的雪水当量 (SWE) 和2–3月局地土壤温度 (ST). SWE的正异常会触发异常东传的Rossby波, 导致下游出现位势高度负异常并引起降温. 通过雪和温度的正反馈, 这种异常低温持续到春季并使得NPP下降. ST与随后季节的温度和降水密切相关, 当ST出现正异常时, 该地区的4–6月温度和降水呈现出东西向偶极子异常分布.对比各方案的预测效果发现, ST比SWE有更好的预测能力. 2009–2014年独立后报结果显示, ST方案对NPP的空间分布和年际变率都有很好的预测效果. 交叉检验的结果显示, 多因子方案中引入ST后能提高模型13 %的预测技巧.

Brown Carbon Fuel and Emission Source Attributions to Global Snow Darkening Effect

AbstractSnow and ice albedo reduction due to deposition of absorbing particles (snow darkening effect [SDE]) warms the Earth system and is largely attributed to black carbon (BC) and dust. Absorbing organic aerosol (BrC) also contributes to SDE but has received less attention due to uncertainty and challenges in model representation. This work incorporates the SDE of absorbing organic aerosol (BrC) from biomass burning and biofuel sources into the Snow Ice and Aerosol Radiative (SNICAR) model within a variant of the Community Earth System Model. Additionally, 12 different emission regions of BrC and BC from biomass burning and biofuel sources are tagged to quantify the relative contribution to global and regional SDE. BrC global SDE (0.021–0.056 Wm−2 over land area and 0.0061–0.016 Wm−2 over global area) is larger than other model estimates, corresponding to 37%–98% of the SDE from BC. When compared to observations, BrC simulations have a range in median bias (−2.5% to +21%), with better agreement in the simulations that include BrC photochemical bleaching. The largest relative contributions to global BrC SDE are traced to Northern Asia (23%–31%), Southeast Asia (16%–21%), and South Africa (13%–17%). Transport from Southeast Asia contributes nearly half of the regional BrC SDE in Antarctica (0.084–0.3 Wm−2), which is the largest regional input to global BrC SDE. Lower latitude BrC SDE is correlated with snowmelt, in‐snow BrC concentrations, and snow cover fraction, while polar BrC SDE is correlated with surface insolation and snowmelt. This indicates the importance of in‐snow processes and snow feedbacks on modeled BrC SDE.

Improved Simulation of Arctic Circumpolar Land Area Snow Properties and Soil Temperatures

The impact of high latitude climate warming on Arctic snow cover and its insulating properties has key implications for the surface and soil energy balance. Few studies have investigated specific trends in Arctic snowpack properties because there is a lack of long-term in situ observations and current detailed snow models fail to represent the main traits of Arctic snowpacks. This results in high uncertainty in modeling snow feedbacks on ground thermal regime due to induced changes in snow insulation. To better simulate Arctic snow structure and snow thermal properties, we implemented new parameterizations of several snow physical processes—including the effect of Arctic low vegetation and wind on snowpack—in the Crocus detailed snowpack model. Significant improvements compared to standard Crocus snow simulations and ERA-Interim (ERAi) reanalysis snow outputs were observed for a large set of in-situ snow data over Siberia and North America. Arctic Crocus simulations produced improved Arctic snow density profiles over the initial Crocus version, leading to a soil surface temperature bias of −0.5 K with RMSE of 2.5 K. We performed Crocus simulations over the past 39 years (1979–2018) for circumpolar taiga (open forest) and pan-Arctic areas at a resolution of 0.5°, driven by ERAi meteorological data. Snowpack properties over that period feature significant increase in spring snow bulk density (mainly in May and June), a downward trend in snow cover duration and an upward trend in wet snow (mainly in spring and fall). The pan-Arctic maximum snow water equivalent shows a decrease of −0.33 cm dec−1. With the ERAi air temperature trend of +0.84 K dec−1 featuring Arctic winter warming, these snow property changes have led to an upward trend in soil surface temperature (Tss) at a rate of +0.41 K dec−1 in winter. We show that the implemented snowpack property changes increased the Tss trend by 36% compared to the standard simulation. Winter induced changes in Tss led to a significant increase of 16% (+4 cm dec−1) in the estimated active layer thickness (ALT) over the past 39 years. An increase in ALT could have a significant impact on permafrost evolution, Arctic erosion and hydrology.

Impact of Snow Initialization in Subseasonal‐to‐Seasonal Winter Forecasts With the Norwegian Climate Prediction Model

AbstractSnow initialization has been previously investigated as a potential source of predictability at the subseasonal‐to‐seasonal (S2S) timescale in winter and spring, through its local radiative, thermodynamical, and hydrological feedbacks. However, previous studies were conducted with low‐top models over short periods only. Furthermore, the potential role of the land surface‐stratosphere connection upon the S2S predictability had remained unclear. To this end, we have carried out twin 30‐member ensembles of 2‐month (November and December) retrospective forecasts over the period 1985–2016, with either realistic or degraded snow initialization. A high‐top version of the Norwegian Climate Prediction Model is used, based on the Whole Atmosphere Community Climate Model, to insure improved coupling with the stratosphere. In a composite difference of high versus low initial Eurasian snow, the surface temperature is strongly impacted by the presence of snow, and wave activity fluxes into the stratosphere are enhanced at a 1‐month lag, leading to a weakened polar vortex. Focusing further on 7 years characterized by a strongly negative phase of the Arctic Oscillation, we find a weak snow feedback contributing to the maintenance of the negative Arctic Oscillation. By comparing the twin forecasts, we extracted the predictive skill increment due to realistic snow initialization. The prediction of snow itself is greatly improved, and there is increased skill in surface temperature over snow‐covered land in the first 10 days, and localized skill increments in the mid‐latitude transition regions on the southern flanks of the snow‐covered land areas, at lead times longer than 30 days.

Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations.

Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results.

Future climate projection under IPCC A1B scenario in the source region of Yellow River with complex topography using RegCM3

AbstractLocated on the Tibetan Plateau, the source region of Yellow River has experienced remarkable climate change over past a few decades, which affects the regional ecosystem, agricultural development, and water availability. In this paper, high‐resolution RegCM3 driven by ECHAM5 is applied to generate both control climate for 1980–2000 and regional climate projections for the 21st century (2010–2098) under the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario. For control climate, RegCM3 can well reproduce the spatial patterns of precipitation and surface air temperature with more detailed representation of fine scale topography. Wet and cold biases are produced in the simulation, but overall improvement by RegCM3 is evident compared to the driving global climate model (GCM) of ECHAM5. In the future projection, the model demonstrates significant warming over the whole analysis domain. Precipitation on the other hand shows mixed signals of reduction and increase over simulation domain, while the areas of precipitation reduction extend with increasing integration time and finally cover most parts of the domain at the end of 21st century. As projection time increases, high altitude region will experience more precipitation reduction in summer and less reduction or even increase in winter. The winter warming at the high elevation area gets more evident than that at the low elevation area, which may be due to the snow feedback. Analyzing the change of probability distributions of surface climate, it can be concluded that the frequency of heavy precipitation in winter tends to increase with time indicating more extreme precipitation events in the future. The spectrum of temperature probability density functions (PDFs) moves toward higher end.

Northern Hemispheric cryosphere response to volcanic eruptions in the Paleoclimate Modeling Intercomparison Project 3 last millennium simulations

AbstractWe analyzed last millennium simulations (circa 850–1850 Common Era) from the Paleoclimate Modeling Intercomparison Project 3 (PMIP3) project to determine whether current state‐of‐the‐art models produce sudden changes and persistence of cold conditions after large volcanic eruptions as inferred from geological records and previous climate modeling. Snow cover over Baffin Island in the eastern Canadian Arctic shows large‐scale expansion (as seen in proxy records) in two of the five models with snow cover information available, although it is not sustained beyond a decade. Sea ice expansion in the North Atlantic is seen in some PMIP3 models after large eruptions, although none of these models produce significant centennial‐scale effects. Warm Baffin Island summer climates stunt snow expansion in some models completely, and model topography tends to miss the critical plateau elevations that could sustain snow on the island. Northern Hemisphere sea ice extent is lower in six of the eight models than in reconstructions over the past millennium. Annual average Northern Hemisphere mean climates have a range of 3 K across models, while Arctic summer land‐only climates span more than 6 K. This has critical consequences on ice and snow formation and persistence in regions such as the Arctic where temperatures are near the freezing point and small temperature changes affect ice and snow feedback that could induce further climate changes. Thus, it is critical that models accurately represent absolute temperature.

Change in snow phenology and its potential feedback to temperature in the Northern Hemisphere over the last three decades

Trends in the duration or extent of snow cover are expected to feedback to temperature trends. We analyzed trends in dates of onset and termination of snow cover in relation to temperature over the past 27 years (1980–2006) from over 636 meteorological stations in the Northern Hemisphere. Different trends in snow duration are observed over North America and Eurasia. Over North America, the termination date of snow cover remained stable during the 27 years, whereas over Eurasia it has advanced by 2.6 ± 5.6 d decade−1. Earlier snow cover termination is systematically correlated on a year-to-year basis with a positive temperature anomaly during the snowmelt month with a sensitivity of −0.077 °C d−1. These snow feedbacks to air temperature are more important in spring, because high net radiation is coupled with thin snow cover.

Global, regional and local scale factors determining glaciation extent in Eastern Siberia over the last 140,000 years

The aim of this work is to evaluate the effect of variations of greenhouse gas concentrations, orbital parameters, sea-surface conditions, vegetation and dust deposition on the extent of East Siberian mountain glaciations during the late Quaternary. An atmosphere-only general circulation model is used in a series of 16 sensitivity tests at high spatial resolution over the region of interest to systematically evaluate the relative importance of these different forcing parameters. No attempt was made to reproduce in detail the history of late Quaternary mountain glaciations in East Siberia, because, given (a) the temporal and spatial scarcity of available evidence of mountain glaciations in this region and (b) the large uncertainties concerning the boundary conditions to be prescribed in this model, such an exercise must necessarily remain incomplete and partially inconclusive. The results of this study suggest that moisture delivery from the Atlantic is an important factor determining mountain glacier mass balance in Eastern Siberia and is very sensitive to the geometry of the West Eurasian ice sheet. This means that variable moisture blocking by the West Eurasian ice sheet during the Weichselian is the most important single factor explaining the opposite history of glacier and ice sheet extent in West and East Eurasia during the Weichselian. This work confirms earlier results showing that the large 140 kyr BP West Eurasian ice sheet caused regional-scale cooling extending towards Eastern Eurasia. Nevertheless, the simulated response of the regional summer temperature (and thus glacier extent because of the strong dependency of glacier mass balance of summer melt rates) is to a very large extent directly determined by insolation. For the Early Weichselian, this leads to a clear maximum of local glacier extent at 70 kyr BP, which is in line with the variations of top-of-the-atmosphere insolation on orbital time scales, but to some degree at odds with geological evidence which suggests larger glacier extent at 115 and 90 kyr BP than at 70 kyr BP. Through snow feedbacks, the effects of changes in the prescribed vegetation distribution and dust deposition rate are also substantial. In summary, it appears that the broad features of late Quaternary glaciation history in Eastern Eurasia can be understood in terms of known forcings.

Assessment of regional seasonal rainfall predictability using the CPTEC/COLA atmospheric GCM

This is a study of the annual and interannual variability of regional rainfall produced by the Center for Weather Forecasts and Climate Studies/Center for Ocean, Land and Atmospheric Studies (CPTEC/COLA) atmospheric global climate model. An evaluation is made of a 9-member ensemble run of the model forced by observed global sea surface temperature (SST) anomalies for the 10-year period 1982–1991. The Brier skill score and, Relative Operating Characteristics (ROC) are used to assess the predictability of rainfall and to validate rainfall simulations, in several regions world wide. In general, the annual cycle of precipitation is well simulated by the model for several continental and oceanic regions in the tropics and mid latitudes. Interannual variability of rainfall during the peak rainy season is realistically simulated in Northeast Brazil, Amazonia, central Chile, and southern Argentina–Uruguay, Eastern Africa, and tropical Pacific regions, where the model shows good skill. Some regions, such as northwest Peru–Ecuador, and southern Brazil exhibit a realistic simulation of rainfall anomalies associated with extreme El Nino warming conditions, while in years with neutral or La Nina conditions, the agreement between observed and simulated rainfall anomalies is not always present. In the monsoon regions of the world and in southern Africa, even though the model reproduces the annual cycle of rainfall, the skill of the model is low for the simulation of the interannual variability. This is indicative of mechanisms other than the external SST forcing, such as the effect of land–surface moisture and snow feedbacks or the representation of sub-grid scale processes, indicating the important role of factors other than external boundary forcing. The model captures the well-known signatures of rainfall anomalies of El Nino in 1982–83 and 1986–87, indicating its sensitivity to strong external forcing. In normal years, internal climate variability can affect the predictability of climate in some regions, especially in monsoon areas of the world.

Analysis of snow feedbacks in 14 general circulation models

Snow feedbacks produced by 14 atmospheric general circulation models have been analyzed through idealized numerical experiments. Included in the analysis is an investigation of the surface energy budgets of the models. Negative or weak positive snow feedbacks occurred in some of the models, while others produced strong positive snow feedbacks. These feedbacks are due not only to melting snow, but also to increases in boundary temperature, changes in air temperature, changes in water vapor, and changes in cloudiness. As a result, the net response of each model is quite complex. We analyze in detail the responses of one model with a strong positive snow feedback and another with a weak negative snow feedback. Some of the models include a temperature dependence of the snow albedo, and this has significantly affected the results.

Hemispheric snow cover from satellites

Full hemispheric monitoring of snow cover has been possible since the advent of meteorological satellites in the 1960s. Since that time visible satellite imagery has been used to chart the extent of northern hemisphere snow on a weekly basis. An analysis of monthly snow areas from a consistent U.S. National Oceanic and Atmospheric Administration (NOAA) set, dating back to 1972, finds that hemispheric snow cover has been well below means for the 1972–91 interval since the middle of 1987. Since the late 1970s multichannel data from satellite-borne passive microwave sensors have been used to estimate hemispheric snowpack extent and depth or water equivalent. Microwave extents generally run considerably lower than NOAA visible values due to microwave difficulties in detecting patchy or wet snow, snow lying on unfrozen ground, and snow in forested regions. The relative simplicity of observing hemispheric snow cover from satellites, the potential of integrating these and other sources of data using geographical information system techniques, the critical role that snow cover has in the global heat budget, and the expected role of snow feedbacks in anthropogenic climate change support the continued diligent monitoring of snow cover.

Hemispheric snow cover from satellites

Full hemispheric monitoring of snow cover has been possible since the advent of meteorological satellites in the 1960s. Since that time visible satellite imagery has been used to chart the extent of northern hemisphere snow on a weekly basis. An analysis of monthly snow areas from a consistent U.S. National Oceanic and Atmospheric Administration (NOAA) set, dating back to 1972, finds that hemispheric snow cover has been well below means for the 1972–91 interval since the middle of 1987. Since the late 1970s multichannel data from satellite-borne passive microwave sensors have been used to estimate hemispheric snowpack extent and depth or water equivalent. Microwave extents generally run considerably lower than NOAA visible values due to microwave difficulties in detecting patchy or wet snow, snow lying on unfrozen ground, and snow in forested regions. The relative simplicity of observing hemispheric snow cover from satellites, the potential of integrating these and other sources of data using geographical information system techniques, the critical role that snow cover has in the global heat budget, and the expected role of snow feedbacks in anthropogenic climate change support the continued diligent monitoring of snow cover.

Interpretation of Snow-Climate Feedback as Produced by 17 General Circulation Models

Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer Earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

Ice and Snow Feedbacks and the Latitudinal and Seasonal Distribution of Climate Sensitivity

Abstract A new parameterization of snow and ice area and albedo as functions of surface temperature is presented based on recent satellite observations of snow and ice extent. This parameterization is incorporated into a seasonal energy-balance climate model. Experiments are conducted with the model to determine the effects of this parameterization change on the latitudinal and seasonal distribution of model sensitivity to external forcings of climate change, such as solar constant variations and changes in the atmospheric carbon dioxide amount. The sea ice-thermal inertia feedback is found to be the determining factor in this sensitivity pattern, producing enhanced sensitivity in the polar regions in the winter and decreased sensitivity in the polar regions in the summer. The albedo feedbacks (snow-area and snow/ice-meltwater) are weak and produce a small amount of additional sensitivity, but do not change the pattern. The response pattern is the same as that found by Manabe and Stouffer (1980) with a ge...