Rapid vegetation responses and feedbacks amplify climate model response to snow cover changes

Abstract. We applied a Regional Climate Model (RCM) to simulate precipitation and snow cover over the Himalaya, between March 2000 and December 2002. Due to its higher resolution, our model simulates a more realistic spatial variability of wind and precipitation than those of the reanalysis of the European Centre of Medium range Weather Forecast (ECMWF) used as lateral boundaries. In this region, we found very large discrepancies between the estimations of precipitation provided by reanalysis, rain gauges networks, satellite observations, and our RCM simulation. Our model clearly underestimates precipitation at the foothills of the Himalaya and in its eastern part. However, our simulation provides a first estimation of liquid and solid precipitation in high altitude areas, where satellite and rain gauge networks are not very reliable. During the two years of simulation, our model resembles the snow cover extent and duration quite accurately in these areas. Both snow accumulation and snow cover duration differ widely along the Himalaya: snowfall can occur during the whole year in western Himalaya, due to both summer monsoon and mid-latitude low pressure systems bringing moisture into this region. In Central Himalaya and on the Tibetan Plateau, a much more marked dry season occurs from October to March. Snow cover does not have a pronounced seasonal cycle in these regions, since it depends both on the quite variable duration of the monsoon and on the rare but possible occurrence of snowfall during the extra-monsoon period.

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How detailed do cloud microphysics need to be in climate models?

10.5194/egusphere-egu21-7115 ◽

2021 ◽

Author(s):

Ulrike Proske ◽

Sylvaine Ferrachat ◽

David Neubauer ◽

Ulrike Lohmann

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Computing Time ◽

Cloud Microphysics ◽

Model Response ◽

Microphysical Processes ◽

Improved Accuracy

Clouds are of major importance for the climate system, but the radiative forcing resulting from their interaction with aerosols remains uncertain. To improve the representation of clouds in climate models, the parameterisations of cloud microphysical processes (CMPs) have become increasingly detailed. However, more detailed climate models do not necessarily result in improved accuracy for estimates of radiative forcing (Knutti and Sedl&#225;&#269;ek, 2013; Carslaw et al., 2018). On the contrary, simpler formulations are cheaper, sufficient for some applications, and allow for an easier understanding of the respective process' effect in the model.This study aims to gain an understanding which CMP parameterisation complexity is sufficient through simplification. We gradually phase out processes such as riming or aggregation from the global climate model ECHAM-HAM, meaning that the processes are only allowed to exhibit a fraction of their effect on the model state. The shape of the model response as a function of the artificially scaled effect of a given process helps to understand the importance of this process for the model response and its potential for simplification. For example, if partially removing a process induces only minor alterations in the present day climate, this process presents as a good candidate for simplification. This may be then further investigated, for example in terms of computing time. The resulting sensitivities to CMP complexity are envisioned to guide CMP model simplifications as well as steer research towards those processes where a more accurate representation proves to be necessary.&#160; Carslaw, Kenneth, Lindsay Lee, Leighton Regayre, and Jill Johnson (Feb. 2018). &#8220;Climate Models Are Uncertain, but We Can Do Something About It&#8221;. In: Eos 99. doi: 10.1029/2018EO093757Knutti, Reto and Jan Sedl&#225;&#269;ek (Apr. 2013). &#8220;Robustness and Uncertainties in the New CMIP5 Climate Model Projections&#8221;. In: Nature Climate Change 3.4, pp. 369&#8211;373. doi: 10.1038/nclimate1716

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Evaluation of CLASS Snow Simulation over Eastern Canada

Journal of Hydrometeorology ◽

10.1175/jhm-d-16-0153.1 ◽

2017 ◽

Vol 18 (5) ◽

pp. 1205-1225 ◽

Cited By ~ 19

Author(s):

Diana Verseghy ◽

Ross Brown ◽

Libo Wang

Keyword(s):

Snow Cover ◽

Land Surface ◽

Snow Water Equivalent ◽

Climate Model ◽

Regional Climate ◽

Eastern Canada ◽

Fractional Snow Cover ◽

Forest Regions ◽

Snow Water ◽

Snow Model

Abstract The Canadian Land Surface Scheme (CLASS), version 3.6.1, was run offline for the period 1990–2011 over a domain centered on eastern Canada, driven by atmospheric forcing data dynamically downscaled from ERA-Interim using the Canadian Regional Climate Model. The precipitation inputs were adjusted to replicate the monthly average precipitation reported in the CRU observational database. The simulated fractional snow cover and the surface albedo were evaluated using NOAA Interactive Multisensor Snow and Ice Mapping System and MODIS data, and the snow water equivalent was evaluated using CMC, Global Snow Monitoring for Climate Research (GlobSnow), and Hydro-Québec products. The modeled fractional snow cover agreed well with the observational estimates. The albedo of snow-covered areas showed a bias of up to −0.15 in boreal forest regions, owing to neglect of subgrid-scale lakes in the simulation. In June, conversely, there was a positive albedo bias in the remaining snow-covered areas, likely caused by neglect of impurities in the snow. The validation of the snow water equivalent was complicated by the fact that the three observation-based datasets differed widely. Also, the downward adjustment of the forcing precipitation clearly resulted in a low snow bias in some regions. However, where the density of the observations was high, the CLASS snow model was deemed to have performed well. Sensitivity tests confirmed the satisfactory behavior of the current parameterizations of snow thermal conductivity, snow albedo refreshment threshold, and limiting snow depth and underlined the importance of snow interception by vegetation. Overall, the study demonstrated the necessity of using a wide variety of observation-based datasets for model validation.

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Contribuições do segundo e do terceiro modos internos de gravidade para a resposta do movimento vertical

Anuário do Instituto de Geociências - UFRJ ◽

10.11137/2008_2_50-52 ◽

2008 ◽

Vol 31 (2) ◽

pp. 50-52

Author(s):

Julio Buchmann

Keyword(s):

Climate Model ◽

Normal Modes ◽

Vertical Motion ◽

Real Data ◽

Primitive Equations ◽

Tropical Atlantic ◽

Motion Response ◽

Atmospheric Research ◽

East Pacific ◽

Model Response

In earlier papers of a series of real data integrations of the National Center for Atmospheric Research Community Climate Model with tropical heat anomalies display regions of pronounced subsidence and drying located several thousand kilometers westward poleward of the heating for cases of tropical Atlantic heating and tropical east Pacific heating. This highly predictable sinking response is established within the first five days of these integrations. The normal-modes of a set of adiabatic primitive equations linearized about a basic state at rest are used to partition model response into gravity-inertia and Rossby modes. The most important contribution for the vertical motion response comes from the gravity modes added for all vertical modes. The principal emphasis is given upon the contributions of the second and third internal vertical modes (with equivalent depths on the order of a fews hundred meters) for the vertical motion response

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Comparison of Snow Cover Observations along the Tateyama-Kurobe Alpine Route with Snow Cover Simulations Using the Non-hydrostatic Regional Climate Model (NHRCM) with Different Horizontal Resolutions

Journal of Geography (Chigaku Zasshi) ◽

10.5026/jgeography.128.77 ◽

2019 ◽

Vol 128 (1) ◽

pp. 77-92 ◽

Cited By ~ 3

Author(s):

Hiroaki KAWASE ◽

Hajime IIDA ◽

Kazuma AOKI ◽

Wataru SHIMADA ◽

Masaya NOSAKA ◽

...

Keyword(s):

Regional Climate Model ◽

Snow Cover ◽

Climate Model ◽

Regional Climate

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Contrasting seasonal changes in temperature, precipitation and snow cover simulated over the European Alps during the twentieth century

10.5194/egusphere-egu21-11097 ◽

2021 ◽

Author(s):

Martin Ménégoz ◽

Julien Beaumet ◽

Hubert Gallée ◽

Xavier Fettweis ◽

Samuel Morin ◽

...

Keyword(s):

Snow Cover ◽

Snow Water Equivalent ◽

Climate Model ◽

Decadal Variability ◽

Regional Climate ◽

Horizontal Resolution ◽

Glacier Mass Balance ◽

European Alps ◽

Climate Trends ◽

The Alps

The evolution of temperature, precipitation and snow cover in the European Alps have been simulated with the regional climate model MAR applied with a 7 kilometre horizontal resolution and driven by the ERA-20C (1902-2010) and the ERA5 reanalyses (1981-2018). A comparison with observational datasets, including French and Swiss local meteorological stations, in-situ glacier mass balance measurements and reanalysis product demonstrates high model skill for snow cover duration and snow water equivalent (SWE) as well as for the climatology and the inter-annual variability of both temperature and precipitation. The relatively high resolution allows to estimate the meteorological variables up to 3000m.a.s.l. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km-1 (1.21 mmd-1.km-1) in summer and 38%km-1 (1.15mmd mmd-1.km-1) in winter, on average over 1971&#8211;2008 and shows a large spatial variability. This study evidences seasonal and altitudinal contrasts of climate trends over the Alps. A significant (pvalue< 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903&#8211;2010, with changes typically reaching 20% to 40% per century, a signal strongly modulated by multi-decadal variability during the second part of the century. A general drying is found in summer over the same period, exceeding 20% to 30% per century in the western plains and 40% to 50% per century in the southern plains surrounding the Alps but remaining smaller (<10%) and not significant above 1500ma.s.l. Over 1903&#8211;2010, the maximum of daily precipitation (Rx1day) shows a general and significant increase at the annual timescale and also during the four seasons, reaching local values between 20% and 40% per century over large parts of the Alps and the Apennines. Trends of Rx1day are significant (pvalue<0.05) only when considering long time series, typically 50 to 80 years depending on the area considered. Some of these trends are nonetheless significant when computed over 1970&#8211;2010, suggesting a recent acceleration of the increase in extreme precipitation. Rx1day increase occurs where the annual correlation between temperature and intense precipitation is high. The highest warming rates in MAR are found at low elevations (< 1000 m a.s.l) in winter, whereas they are found at high elevations (> 2000 m a.s.l) in summer. In spring, warming trends show a maximum at intermediate elevations (1500 m to 1800 m). Our results suggest that higher warming at these elevations is mostly linked with the snow-albedo feedback in spring and summer.

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Climate Data to Undertake Hygrothermal and Whole Building Simulations Under Projected Climate Change Influences for 11 Canadian Cities

Data ◽

10.3390/data4020072 ◽

2019 ◽

Vol 4 (2) ◽

pp. 72 ◽

Cited By ~ 4

Author(s):

Abhishek Gaur ◽

Michael Lacasse ◽

Marianne Armstrong

Keyword(s):

Climate Change ◽

Snow Cover ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Internal Variability ◽

Climatic Conditions ◽

Climate Data ◽

Wide Range ◽

The Future

Buildings and homes in Canada will be exposed to unprecedented climatic conditions in the future as a consequence of global climate change. To improve the climate resiliency of existing and new buildings, it is important to evaluate their performance over current and projected future climates. Hygrothermal and whole building simulation models, which are important tools for assessing performance, require continuous climate records at high temporal frequencies of a wide range of climate variables for input into the kinds of models that relate to solar radiation, cloud-cover, wind, humidity, rainfall, temperature, and snow-cover. In this study, climate data that can be used to assess the performance of building envelopes under current and projected future climates, concurrent with 2 °C and 3.5 °C increases in global temperatures, are generated for 11 major Canadian cities. The datasets capture the internal variability of the climate as they are comprised of 15 realizations of the future climate generated by dynamically downscaling future projections from the CanESM2 global climate model and thereafter bias-corrected with reference to observations. An assessment of the bias-corrected projections suggests, as a consequence of global warming, future increases in the temperatures and precipitation, and decreases in the snow-cover and wind-speed for all cities.

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Sensitivity and Interdependency Analysis of the HBV Conceptual Model Parameters in a Semi-Arid Mountainous Watershed

Water ◽

10.3390/w12092440 ◽

2020 ◽

Vol 12 (9) ◽

pp. 2440

Author(s):

Hamza Ouatiki ◽

Abdelghani Boudhar ◽

Aziz Ouhinou ◽

Abdelaziz Beljadid ◽

Marc Leblanc ◽

...

Keyword(s):

Snow Cover ◽

Conceptual Model ◽

Water Resource Management ◽

Optimal Parameter ◽

Field Capacity ◽

Temperature Correction ◽

Model Parameters ◽

Daily Streamflow ◽

Model Response ◽

Semi Arid

Hydrological models, with different levels of complexity, have become inherent tools in water resource management. Conceptual models with low input data requirements are preferred for streamflow modeling, particularly in poorly gauged watersheds. However, the inadequacy of model structures in the hydrologic regime of a given watershed can lead to uncertain parameter estimation. Therefore, an understanding of the model parameters’ behavior with respect to the dominant hydrologic responses is of high necessity. In this study, we aim to investigate the parameterization of the HBV (Hydrologiska Byråns Vattenbalansavedelning) conceptual model and its influence on the model response in a semi-arid context. To this end, the capability of the model to simulate the daily streamflow was evaluated. Then, sensitivity and interdependency analyses were carried out to identify the most influential model parameters and emphasize how these parameters interact to fit the observed streamflow under contrasted hydroclimatic conditions. The results show that the HBV model can fairly reproduce the observed daily streamflow in the watershed of interest. However, the reliability of the model simulations varies from one year to another. The sensitivity analysis showed that each of the model parameters has a certain degree of influence on model behavior. The temperature correction factor (ETF) showed the lowest effect on the model response, while the sensitivity to the degree-day factor (DDF) highly depends on the availability of snow cover. Overall, the changes in hydroclimatic conditions were found to be mostly responsible for the annual variability of the optimal parameter values. Additionally, these changes seem to actuate the interdependency between the parameters of the soil moisture and the response routines, particularly Field Capacity (FC), the recession coefficient K0, the percolation coefficient (KPERC), and the upper reservoir threshold (UZL). The latter combines either to shrink the storage capacity of the model’s reservoirs under extremely high peak flows or to enlarge them under overestimated water supply, mainly provoked by abundant snow cover.

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