scholarly journals Snow cover sensitivity to black carbon deposition in the Himalaya: from atmospheric and ice core measurements to regional climate simulations

2013 ◽  
Vol 13 (11) ◽  
pp. 31013-31040
Author(s):  
M. Ménégoz ◽  
G. Krinner ◽  
Y. Balkanski ◽  
O. Boucher ◽  
A. Cozic ◽  
...  

Abstract. We applied a climate-chemistry model to evaluate the impact of black carbon (BC) deposition on the Himalayan snow cover from 1998 to 2008. Using a stretched grid with a resolution of 50 km over this complex topography, the model reproduces reasonably well the observations of both the snow cover duration and the seasonal cycle of the atmospheric BC concentration including a maximum in atmospheric BC during the pre-monsoon period. Comparing the simulated BC concentrations in the snow with observations is challenging because of the high spatial variability and the complex vertical distribution of BC in the snow. We estimate that both wet and dry BC depositions affect the Himalayan snow cover reducing its annual duration by one to eight days. The resulting increase of the net shortwave radiation at the surface reaches an annual mean of 1 to 3 W m−2, leading to a localised warming of 0.05 to 0.3 °C.

2014 ◽  
Vol 14 (8) ◽  
pp. 4237-4249 ◽  
Author(s):  
M. Ménégoz ◽  
G. Krinner ◽  
Y. Balkanski ◽  
O. Boucher ◽  
A. Cozic ◽  
...  

Abstract. We applied a climate-chemistry global model to evaluate the impact of black carbon (BC) deposition on the Himalayan snow cover from 1998 to 2008. Using a stretched grid with a resolution of 50 km over this complex topography, the model reproduces reasonably well the remotely sensed observations of the snow cover duration. Similar to observations, modelled atmospheric BC concentrations in the central Himalayas reach a minimum during the monsoon and a maximum during the post- and pre-monsoon periods. Comparing the simulated BC concentrations in the snow with observations is more challenging because of their high spatial variability and complex vertical distribution. We simulated spring BC concentrations in surface snow varying from tens to hundreds of μg kg−1, higher by one to two orders of magnitude than those observed in ice cores extracted from central Himalayan glaciers at high elevations (>6000 m a.s.l.), but typical for seasonal snow cover sampled in middle elevation regions (<6000 m a.s.l.). In these areas, we estimate that both wet and dry BC depositions affect the Himalayan snow cover reducing its annual duration by 1 to 8 days. In our simulations, the effect of anthropogenic BC deposition on snow is quite low over the Tibetan Plateau because this area is only sparsely snow covered. However, the impact becomes larger along the entire Hindu-Kush, Karakorum and Himalayan mountain ranges. In these regions, BC in snow induces an increase of the net short-wave radiation at the surface with an annual mean of 1 to 3 W m−2 leading to a localised warming between 0.05 and 0.3 °C.


2020 ◽  
Author(s):  
Marion Réveillet ◽  
Marie Dumont ◽  
Simon Gascoin ◽  
Pierre Nabat ◽  
Matthieu Lafaysse ◽  
...  

&lt;p&gt;Light absorbing particles such as black carbon(BC) or mineral dust are known to darken the snow surface when deposited on the snow cover and amplify several snow-albedo feedbacks, drastically modifying the snowpack evolution and the snow cover duration. Mineral dust deposition on snow is generally more variablein time than black carbon deposition and can exhibit both a high inter and intra annual variability. In France, the Alps and the Pyrenees mountain ranges are affected by large dust deposition events originating from the Sahara . The aim of this study is to quantify the impact of these impurities on the snow cover variability over the last 39 years (1979-2018).&lt;/p&gt;&lt;p&gt;For that purpose, the detailed snowpack model Crocus with an explicit representation of impurities is forced by SAFRAN meteorological reanalysis and a downscaling of the simulated deposition fluxes from a regional climate model (ALADIN-Climate). Different simulations are performed: (i) considering dust and/or BC (i.e. explicit representation), (ii) without impurities and (iii) considering an implicit representation (i.e. empirical parameterization based on a decreasing law of the albebo with snow age).&lt;/p&gt;&lt;p&gt;Simulations are compared at point scale to the snow depth measured at more than 200 Meteo-France&amp;#8217;s stations in each massif, and spatially evaluated over the 2000-2018 period in comparing thesnow cover area, snow cover duration and the Jacard index to MODIS snow products. Scores are generally better when considering the explicit representation of the impurities than when using the snow age as a proxy for light absorbing particles content.&lt;/p&gt;&lt;p&gt;Results indicate that dust and BC have a significant impact on the snow cover duration with strong variations in the magnitude of the impact from one year to another and from one location to another.We also investigate the contribution of light absorbing particles depositionto snow cover inter-annual variability based on statistical approaches.&lt;/p&gt;


2014 ◽  
Vol 8 (5) ◽  
pp. 5035-5076 ◽  
Author(s):  
H.-W. Jacobi ◽  
S. Lim ◽  
M. Ménégoz ◽  
P. Ginot ◽  
P. Laj ◽  
...  

Abstract. Black carbon (BC) in the snow in the Himalayas has recently attracted considerable interest due to its impact on snow albedo, snow and glacier melting, regional climate and water resources. A single particle soot photometer (SP2) instrument was used to measure refractory BC (rBC) in a series of surface snow samples collected in the upper Khumbu Valley in Nepal between November 2009 and February 2012. The obtained time series indicates annual cycles with maximum concentration before the onset of the monsoon season and fast decreases in rBC during the monsoon period. Measured concentrations ranged from a few ppb up to 70 ppb rBC. However, due to the handling of the samples the measured concentrations possess rather large uncertainties. Detailed modeling of the snowpack including the measured range and an estimated upper limit of rBC concentrations was performed to study the role of BC in the seasonal snowpack. Simulations were performed for three winter seasons with the snowpack model Crocus including a detailed description of the radiative transfer inside the snowpack. While the standard Crocus model strongly overestimates the height and the duration of the seasonal snowpack, a better calculation of the snow albedo with the new radiative transfer scheme enhanced the representation of the snow. However, the period with snow on the ground neglecting BC in the snow was still over-estimated between 37 and 66 days, which was further diminished by 8 to 15% and more than 40% in the presence of 100 or 300 ppb of BC. Compared to snow without BC the albedo is on average reduced by 0.027 and 0.060 in the presence of 100 and 300 ppb BC. While the impact of increasing BC in the snow on the albedo was largest for clean snow, the impact on the local radiative forcing is the opposite. Here, increasing BC caused an even larger impact at higher BC concentrations. This effect is related to an accelerated melting of the snowpack caused by a more efficient metamorphism of the snow due to an increasing size of the snow grains with increasing BC concentrations. The melting of the winter snowpack was shifted by 3 to 10 days and 17 to 27 days during the three winter seasons in the presence of 100 and 300 ppb BC compared to clean snow, while the simulated annual local radiative forcing corresponds to 3 to 4.5 and 10.5 to 13.0 W m−2. An increased sublimation or evaporation of the snow reduces the simulated radiative forcing leading to a net forcing that is lower by 0.5 to 1.5 W m−2, while the addition of 10 ppm dust causes an increase of the radiative forcing between 2.5 and 3 W m−2. According to the simulations 7.5 ppm of dust has an effect equivalent to 100 ppb of BC concerning the impact on the melting of the snowpack and the local radiative forcing.


2015 ◽  
Vol 9 (4) ◽  
pp. 1685-1699 ◽  
Author(s):  
H.-W. Jacobi ◽  
S. Lim ◽  
M. Ménégoz ◽  
P. Ginot ◽  
P. Laj ◽  
...  

Abstract. Black carbon (BC) in snow in the Himalayas has recently attracted considerable interest due to its impact on snow albedo, snow and glacier melting, regional climate and water resources. A single particle soot photometer (SP2) instrument was used to measure refractory BC (rBC) in a series of surface snow samples collected in the upper Khumbu Valley, Nepal between November 2009 and February 2012. The obtained time series indicates annual cycles with maximum rBC concentrations before the onset of the monsoon season and fast decreases during the monsoon period. Detected concentrations ranged from a few up to 70 ppb with rather large uncertainties due to the handling of the samples. Detailed modeling of the snowpack, including the detected range and an estimated upper limit of BC concentrations, was performed to study the role of BC in the seasonal snowpack. Simulations were performed for three winter seasons with the snowpack model Crocus, including a detailed description of the radiative transfer inside the snowpack. While the standard Crocus model strongly overestimates the height and the duration of the seasonal snowpack, a better calculation of the snow albedo with the new radiative transfer scheme enhanced the representation of the snow. However, the period with snow on the ground without BC in the snow was still overestimated between 37 and 66 days, which was further diminished by 8 to 15 % and more than 40 % in the presence of 100 or 300 ppb of BC. Compared to snow without BC, the albedo is reduced on average by 0.027 and 0.060 in the presence of 100 and 300 ppb BC. While the impact of increasing BC in the snow on the albedo was largest for clean snow, the impact on the local radiative forcing is the opposite. Here, increasing BC caused an even larger impact at higher BC concentrations. This effect is related to an accelerated melting of the snowpack caused by a more efficient metamorphism of the snow due to an increasing size of the snow grains with increasing BC concentrations. The melting of the winter snowpack was shifted by 3 to 10 and 17 to 27 days during the three winter seasons in the presence of 100 and 300 ppb BC compared to clean snow, while the simulated annual local radiative forcing corresponds to 3 to 4.5 and 10.5 to 13.0 W m−2. An increased sublimation or evaporation of the snow reduces the simulated radiative forcing, leading to a net forcing that is lower by 0.5 to 1.5 W m−2, while the addition of 10 ppm dust causes an increase of the radiative forcing between 2.5 and 3 W m−2. According to the simulations, 7.5 ppm of dust has an effect equivalent to 100 ppb of BC concerning the impact on the melting of the snowpack and the local radiative forcing.


2013 ◽  
Vol 17 (10) ◽  
pp. 3921-3936 ◽  
Author(s):  
M. Ménégoz ◽  
H. Gallée ◽  
H. W. Jacobi

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.


2014 ◽  
Vol 35 (9) ◽  
pp. 2472-2484 ◽  
Author(s):  
Melissa L. Wrzesien ◽  
Tamlin M. Pavelsky ◽  
Sarah B. Kapnick ◽  
Michael T. Durand ◽  
Thomas H. Painter

2020 ◽  
Author(s):  
Christian Steger ◽  
Jesus Vergara-Temprado ◽  
Nikolina Ban ◽  
Christoph Schär

&lt;p&gt;Weather and climate in alpine areas are strongly modulated by complex topography. Besides its influence on atmospheric flow and thermodynamics (such as orographic precipitation and foehn winds), topography also affects incoming surface radiation in various ways. Direct shortwave radiation might be blocked due to shading effects from neighbouring terrain. Diffuse shortwave radiation can be altered by a reduced sky view factor and reflectance of radiation from surrounding terrain. Similar, the net longwave radiation is affected by emissions from neighbouring terrain.&lt;/p&gt;&lt;p&gt;Radiation in virtually all state-of-the-art weather and climate models is only computed in the vertical direction using the column approximation, and the above-mentioned effects are usually not represented. Still, a few models consider topographic effects by correcting incoming radiation fluxes based on topographic parameters like slope aspect and angle, elevation of horizon, and sky view factor. The Consortium for Small-scale Modeling (COSMO) model includes such a scheme, which is currently only used in the Numerical Weather Prediction mode of the model.&lt;/p&gt;&lt;p&gt;In this study, we apply the surface radiation correction scheme in the climate mode of COSMO. To study its impacts in detail, we force COSMO&amp;#8217;s land-surface model (TERRA) offline with output from a COSMO simulation, which was run without radiation correction at a horizontal resolution of 2.2 km and for a domain covering the Alps. A useful proxy to study the impact of the correction scheme is snow cover duration (SCD), because snow cover length is, amongst other factors, strongly controlled by incoming surface radiation that drives ablation. A comparison of SCD simulated by COSMO with satellite-derived snow cover data (MODIS and AVHRR) reveals a distinctive bias, where SCD is overestimated for south-facing grid cells and underestimated for north-facing cells. Applying the radiation correction in the offline TERRA simulation shows only a moderate reduction of the bias. One reason for this minor improvement is the fact that the topographic parameters are computed from a smoothed digital elevation model (DEM) &amp;#8211; thus the impact of the radiation correction scheme is damped. If topographic parameters are computed from unsmoothed DEM, biases in SCD are further reduced. Currently, further sensitivity experiments are conducted to investigate the effect of computing the topographic parameters from a sub-grid DEM and to assess the energy conservation of the radiation correction scheme.&lt;/p&gt;


2005 ◽  
Vol 18 (1) ◽  
pp. 229-233 ◽  
Author(s):  
S. Vannitsem ◽  
F. Chomé

Abstract The impact of domain size on regional climate simulations is explored in the context of a state-of-the-art regional model centered over western Europe. It is found that the quality of the climate simulations is highly dependent on the domain size. Moreover, the choice of an optimal version is more complex than usually thought, the less appropriate domain having an intermediate size (about 3000 km × 3000 km), and the best versions nearly cover a quarter of the Northern Hemisphere. The use of periodically reinitialized trajectories does improve the climate of suboptimal models but leads to unrealistic dynamical behaviors. The implications for regional climate simulations are briefly discussed.


2017 ◽  
Vol 9 (1) ◽  
pp. 207-222 ◽  
Author(s):  
Philbert Luhunga

AbstractIn this study, the impact of inter-seasonal climate variability on rainfed maize (Zea mays) production over the Wami-Ruvu basin of Tanzania is evaluated. Daily high-resolution climate simulations from the Coordinated Regional Climate Downscaling Experiment_Regional Climate Models (CORDEX_RCMs) are used to drive the Decision Support System for Agro-technological Transfer (DSSAT) to simulate maize yields. Climate simulations for the base period of 35 years (1971–2005) are used to drive DSSAT to simulate maize yields during the historical climate. On the other hand, climate projections for the period 2010–2039 (current), 2040–2069 (mid), and 2070–2099 centuries for two Representative Concentration Pathway (RCP45 and 85) emission scenarios are used to drive DSSAT to simulate maize yields in respective centuries. Statistical approaches based on Pearson correlation coefficient and the coefficients of determination are used in the analysis. Results show that rainfall, maximum temperature, and solar radiation are the most important climate variables that determine variation in rainfed maize yields over the Wami-Ruvu basin of Tanzania. They explain the variability in maize yields in historical climate condition (1971–2005), present century under RCP 4.5, and mid and end centuries under both RCP 4.5 and RCP 8.5.


2015 ◽  
Vol 8 (7) ◽  
pp. 2285-2298 ◽  
Author(s):  
A. I. Stegehuis ◽  
R. Vautard ◽  
P. Ciais ◽  
A. J. Teuling ◽  
D. G. Miralles ◽  
...  

Abstract. Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface scheme, with the goal of detecting the most sensitive physics and identifying those that appear most suitable for simulating the heat wave events of 2003 in western Europe and 2010 in Russia. In total, 55 out of 216 simulations combining different atmospheric physical schemes have a temperature bias smaller than 1 °C during the heat wave episodes, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heat waves, and shortwave radiation is slightly overestimated. Convection is found to be the most sensitive atmospheric physical process impacting simulated heat wave temperature across four different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme configurations, which may be used in the future to perform heat wave analysis and to investigate the impact of climate change during summer in Europe.


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