Improved simulations of snow extent in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2) (original) (raw)
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Evaluation of snow extent and its variability in the Atmospheric Model Intercomparison Project
Journal of Geophysical Research: Atmospheres, 1998
Simulations of monthly mean northern hemisphere snow extent from 27 atmospheric general circulation models (GCMs), run under the auspices of the Atmospheric Model Intercomparison Project (AMIP), are compared to observations. AMIP model runs have common values for sea surface temperatures specified from observations for the decade 1979 through 1988. Here AMIP GCMs are evaluated in terms of their simulations of (1) snow extent over northern hemisphere lands and (2) synoptic conditions associated with extremes in snow extent over particular regions. Observations of snow extent are taken from digitized charts of remotely sensed snow extent from visible imagery provided by the National Oceanic and Atmospheric Administration. In general, AMIP models reproduce a seasonal cycle of snow extent similar to the observed cycle. However, GCMs tend to underestimate fall and winter snow extent (especially over North America) and overestimate spring snow extent (especially over Eurasia). The majority of models display less than half of the observed interannual variability. No temporal correlation is found between simulated and observed snow extent, even when only months with extremely high or low values are considered. These poor correlations indicate that in the models, interannual fluctuations of snow extent are not driven by sea surface temperatures. GCMs are inconsistent in their abilities to simulate synoptic-scale tropospheric circulation patterns associated with extreme snow extent over North American regions, although some models are able to capture many of the observed teleconnection patterns. concentration and solar insolation [Gates, 1992]. Since boundary conditions are largely specified, model results are comparable to each other. In addition, since the boundary conditions are representative of specific calendar years, model results can be directly compared to observations. Hydrological processes in AMIP GCMs have been evaluated by Lau et al. [1996], who found that models generally simulate global precipitation to within 10%-20%. Heavy precipitation associated with deep convection is reasonably estimated, but the
Journal of Hydrometeorology, 2005
Eighteen global atmospheric general circulation models (AGCMs) participating in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2) are evaluated for their ability to simulate the observed spatial and temporal variability in snow mass, or water equivalent (SWE), over North America during the AMIP-2 period (1979–95). The evaluation is based on a new gridded SWE dataset developed from objective analysis of daily snow depth observations from Canada and the United States with snow density estimated from a simple snowpack model. Most AMIP-2 models simulate the seasonal timing and the relative spatial patterns of continental-scale SWE fairly well. However, there is a tendency to overestimate the rate of ablation during spring, and significant between-model variability is found in every aspect of the simulations, and at every spatial scale analyzed. For example, on the continental scale, the peak monthly SWE integrated over the North American continent in AMIP-2 mode...
Simulation of snow mass and extent in general circulation models
Hydrological Processes, 1999
An evaluation of the Biosphere±Atmosphere Transfer Scheme (BATS) snow submodel was conducted, both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). We evaluated, in the stand-alone mode, the performance of BATS parameterizations at local scales using ground-based observations from the former Soviet Union and from Mammoth Mountain, California. The BATS snow scheme reproduces well the seasonal evolution of snow water equivalent in both sites, and the results for the Mammoth Mountain site compare well with those from a more complex, physically based model (SNTHERM). In the coupled mode, we evaluated the modelled snow cover extent, snow mass, precipitation and temperature from BATS as linked to the NCAR CCM3 using available observations. The coupled models capture the broad pattern of seasonal and geographical distribution of snow cover, with better overall performance than the passive microwave snow data derived from the Nimbus-7 Scanning Multi-channel Microwave Radiometer (SMMR) which generally underestimates snow depth. In terms of continents, the snow mass is better simulated during the accumulation period than during the melt period, which is the case for both North America and Eurasia. The simulation of snow mass, precipitation and air temperature for North America is slightly better than that for Eurasia. A rigorous evaluation of snow simulations in coupled land±atmosphere models requires high quality global datasets of snow cover extent, snow depth and snow water equivalent. The available datasets and model outputs are not yet ready to ful®l this objective.
SOLA, 2005
Simulations under present (end of the 20th Century) and future conditions (end of the 21st Century with SRES A1B scenario) by using a 20 km-mesh atmospheric general circulation model (AGCM) over 10 years are conducted and the changes in snow due to global warming are investigated. The seasonal march of the snow cover in the present simulation is comparable to that of satellite-based observational data. Distributions of the simulated snow cover and snow water equivalent (SWE) reflect the detailed geographical features. Due to global warming, the beginning of the snowaccumulating season (the end of the snow-melting season) will occur later (earlier) in most snow regions, and the snow cover will decrease except for very few exceptions. SWE will also decrease in wide areas, but over the cold regions (Siberia and the northern parts of North America), SWE will increase due to increases of snowfall in the coldest season. In both the change and the percentage change of the SWE, we can find that the detailed geographical features effect on them. In Japan, the SWE will decrease over the heavy snow areas. However, the percentage changes are relatively smaller over the colder areas. Recently, the Japan Meteorological Agency and the Meteorological Research Institute succeeded in simulating climate for a period in excess of 10 years using a 20 km-mesh global AGCM for the present (end of the 20 th Century) and future (end of the 21st Century) conditions. The results of the present simulation show, for the most part, good agreement with the observational data in the distributions of precipitation, snow cover and others. This manuscript describes changes in snow cover and SWE due to global warming.
Journal of Geophysical Research, 2009
We investigate the impact of the Eurasian snow cover extent on the Northern Hemisphere winter circulation by performing a suite of ensemble simulations with the Météo-France ''Arpege Climat'' atmospheric general circulation model, spanning 2 decades (1979-2000). Observed snow cover derived from satellite infrared and visible imagery has been forced weekly into the model. Variability in autumn-early winter snow cover extent over eastern Eurasia is linked to circulation anomalies over the North Pacific that are influencing the North Atlantic sector in late winter through the development of the Aleutian-Icelandic Low Seesaw teleconnection. The forcing of realistic snow cover in the model augments potential predictability over eastern Eurasia and the North Pacific and improves the hindcast skill score of the Aleutian-Icelandic Low Seesaw teleconnection. Enhanced eastern Eurasia snow cover is associated with an anomalous upper-tropospheric wave train across Eurasia, anomalously high upward wave activity flux, and a displaced stratospheric polar vortex.
Assessment of Snow Cover and Surface Albedo in the ECHAM5 General Circulation Model
Journal of Climate, 2006
Land surface albedo, snow cover fraction (SCF), and snow depth (SD) from two versions of the ECHAM climate model are compared to available ground-based and remote-sensed climatologies. ECHAM5 accurately reproduces the annual cycle of SD and correctly captures the timing of the snowmelt. ECHAM4, in contrast, simulates an excessive Eurasian snow mass in spring due to a delayed snowmelt. Annual cycles of continental snow cover area (SCA) are captured fairly well in both ECHAM4 and ECHAM5. The negative SCA trend observed during the last two decades of the twentieth century is evident also in the ECHAM5 simulation but less pronounced. ECHAM5 captures the interannual variability of SCA reasonably well, which is in contrast with results that were reported earlier for second-phase Atmospheric Model Intercomparison Project (AMIP II) models. An error analysis revealed that, for studies on SCA, it is essential to test the data records for their homogeneity and trends. The second part of the pa...
Modelled atmospheric response to changes in Northern Hemisphere snow cover
Climate Dynamics, 1996
The surface boundary conditions are altered in a numerical simulation of January climate by prescribing (a) higher and (b) lower than average snow extent over Northern Hemisphere land masses. The anomalies in snow cover are shown to have quite a strong impact on the mean climatic state. Associated with an increase in the areal extent of the snow, there is a significant reduction in temperature throughout the lower troposphere. There are also large increases in sea-level pressure over most land areas. Significant responses in the mass field are also seen at 500 hPa where reductions in atmospheric thickness lead to significant negative anomalies in the height field. Responses are also seen non-locally, over both the North Pacific and North Atlantic basins. The impact of increased snow on cyclone tracks is also examined. A reduction in cyclones is noted over both continents and over the western sectors of both ocean basins. Over the North Atlantic basin this reduction extends across over Europe, significantly weakening the storm track. In the North Pacific, cyclone density is reduced in the west while in the east, there is actually a strengthening of the storm tracks. There are corresponding changes in the genesis of cyclones in both of these regions. The change in cyclogenesis, intensity and density is demonstrated to be associated with changes in baroclinicity between the two experiments. The anomalous snow boundary conditions lead to significant changes in the meridional temperature gradients over both ocean basins which impact on the baroclinic zones.
Hydrological Processes, 2008
Snow is important for water management, and an important component of the terrestrial biosphere and climate system. In this study, the snow models included in the Biome-BGC and Terrestrial Observation and Prediction System (TOPS) terrestrial biosphere models are compared against ground and satellite observations over the Columbia River Basin in the US and Canada and the impacts of differences in snow models on simulated terrestrial ecosystem processes are analysed. First, a point-based comparison of ground observations against model and satellite estimates of snow dynamics are conducted. Next, model and satellite snow estimates for the entire Columbia River Basin are compared. Then, using two different TOPS simulations, the default TOPS model (TOPS with TOPS snow model) and the TOPS model with the Biome-BGC snow model, the impacts of snow model selection on runoff and gross primary production (GPP) are investigated. TOPS snow model predictions were consistent with ground and satellite estimates of seasonal and interannual variations in snow cover, snow water equivalent, and snow season length; however, in the Biome-BGC snow model, the snow pack melted too early, leading to extensive underpredictions of snow season length and snow covered area. These biases led to earlier simulated peak runoff and reductions in summer GPP, underscoring the need for accurate snow models within terrestrial ecosystem models.
Geosciences, 2019
Observed changes in Northern Hemisphere snow cover from satellite records were compared to those predicted by all available Coupled Model Intercomparison Project Phase 5 ("CMIP5") climate models over the duration of the satellite's records, i.e., 1967-2018. A total of 196 climate model runs were analyzed (taken from 24 climate models). Separate analyses were conducted for the annual averages and for each of the seasons (winter, spring, summer, and autumn/fall). A longer record (1922-2018) for the spring season which combines ground-based measurements with satellite measurements was also compared to the model outputs. The climate models were found to poorly explain the observed trends. While the models suggest snow cover should have steadily decreased for all four seasons, only spring and summer exhibited a long-term decrease, and the pattern of the observed decreases for these seasons was quite different from the modelled predictions. Moreover, the observed trends for autumn and winter suggest a long-term increase, although these trends were not statistically significant. Possible explanations for the poor performance of the climate models are discussed.
Improvement of snowpack simulations in a regional climate model
Hydrological Processes, 2011
To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth-generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5-CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5-CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land-surface model. One important cause for the underestimated SWE in Noah is its unrealistic land-surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow-season surface albedo overestimated by MM5-Noah is now more accurately predicted by MM5-CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near-surface cold bias in MM5-Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5-CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5-Noah. In addition, the over-predicted precipitation in the Pacific Northwest as shown in MM5-Noah is significantly decreased in MM5 CLM3 due to the lower evaporation resulting from the longer snow duration.