scholarly journals Snowfall in the Himalayas: an uncertain future from a little-known past

2015 ◽  
Vol 9 (3) ◽  
pp. 1147-1167 ◽  
Author(s):  
E. Viste ◽  
A. Sorteberg
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Reanalysis Data ◽  
Indus Basin ◽  
Data Sets ◽  
Anthropogenic Forcing ◽  
Temperature And Precipitation ◽  
The Mean ◽  
Uncertain Future ◽  
Relative Change

Abstract. Snow and ice provide large amounts of meltwater to the Indus, Ganges and Brahmaputra rivers. This study combines present-day observations and reanalysis data with climate model projections to estimate the amount of snow falling over the basins today and in the last decades of the 21st century. Estimates of present-day snowfall based on a combination of temperature and precipitation from reanalysis data and observations vary by factors of 2–4. The spread is large, not just between the reanalysis and the observations but also between the different observational data sets. With the strongest anthropogenic forcing scenario (RCP8.5), the climate models project reductions in annual snowfall by 30–50% in the Indus Basin, 50–60% in the Ganges Basin and 50–70% in the Brahmaputra Basin by 2071–2100. The reduction is due to increasing temperatures, as the mean of the models show constant or increasing precipitation throughout the year in most of the region. With the strongest anthropogenic forcing scenario, the mean elevation where rain changes to snow – the rain/snow line – creeps upward by 400–900 m, in most of the region by 700–900 meters. The largest relative change in snowfall is seen in the upper westernmost sub-basins of the Brahmaputra. With the strongest forcing scenario, most of this region will have temperatures above freezing, especially in the summer. The projected reduction in annual snowfall is 65–75%. In the upper Indus, the effect of a warmer climate on snowfall is less extreme, as most of the terrain is high enough to have temperatures sufficiently far below freezing today. A 20–40% reduction in annual snowfall is projected.

scholarly journals Snowfall in the Himalayas: an uncertain future from a little-known past

2015 ◽  
Vol 9 (1) ◽  
pp. 441-493 ◽  
Author(s):  
E. Viste ◽  
A. Sorteberg
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Reanalysis Data ◽  
Indus Basin ◽  
Data Sets ◽  
Anthropogenic Forcing ◽  
Temperature And Precipitation ◽  
The Mean ◽  
Uncertain Future ◽  
Relative Change

Abstract. Snow and ice provide large amounts of meltwater to the Indus, Ganges and Brahmaputra rivers. This study combines present-day observations and reanalysis data with climate model projections to estimate the amount of snow falling over the basins today and in the last decades of the 21st century. Estimates of present-day snowfall based on a combination of temperature and precipitation from reanalysis data and observations, vary by factors of 2–4. The spread is large, not just between the reanalysis and the observations, but also between the different observational data sets. With the strongest anthropogenic forcing scenario (RCP 8.5), the climate models project reductions in annual snowfall by 30–50% in the Indus Basin, 50–60% in the Ganges Basin and 50–70% in the Brahmaputra Basin, by 2071–2100. The reduction is due to increasing temperatures, as the mean of the models show constant or increasing precipitation throughout the year in most of the region. With the strongest anthropogenic forcing scenario, the mean elevation where rain changes to snow – the rain/snow line – creeps upward by 400–900 m, in most of the region by 700–900 m. The largest relative change in snowfall is seen in the upper, westernmost sub-basins of the Brahmaputra. With the strongest forcing scenario, most of this region will have temperatures above freezing, especially in the summer. The projected reduction in annual snowfall is 65–75%. In the upper Indus, the effect of a warmer climate on snowfall is less extreme, as most of the terrain is high enough to have temperatures sufficiently far below freezing today. A 20–40% reduction in annual snowfall is projected.

scholarly journals An evaluation of current capabilities of modelling low-frequency climate variability

2016 ◽  
Author(s):  
Heikki Järvinen ◽  
Teija Seitola ◽  
Johan Silén ◽  
Jouni Räisänen
Keyword(s):  
Performance Test ◽  
Climate Models ◽  
Climate Model ◽  
Decadal Variability ◽  
Spectral Power ◽  
Singular Spectrum Analysis ◽  
Surface Air Temperature ◽  
Reanalysis Data ◽  
Data Sets ◽  
Near Surface

Abstract. A crucial performance test of Earth system models is their ability to simulate the climate mean state and variability. Here we concentrate on representation of inter-annual to multi-decadal variability in 12 CMIP5 climate model simulations. Reference climate is provided by two 20th century reanalysis data sets of monthly mean near-surface air temperature. The spectral decomposition is based on Randomised Multi-Channel Singular Spectrum Analysis (RMSSA). The main results are as follows. First, the total spectra for the two reanalysis data sets are remarkably similar in all time scales, except that spectral power of decadal variability (10–30 yr) differ in these data by about 30 %. Second, none of the 12 coupled climate models closely reproduce all aspects of the reference spectra, although some models represent many aspects well. For instance, the IPSL-CM5B-LR model is close to reanalyses but has too little multi-decadal variability, and the HadGEM2-ES model is close to reanalyses except the notable over-activity at periods at and around 10 yr.

scholarly journals Validation of the HIRHAM-Simulated Indian Summer Monsoon Circulation

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Stefan Polanski ◽  
Annette Rinke ◽  
Klaus Dethloff
Keyword(s):  
Summer Monsoon ◽  
Climate Model ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Monsoon Circulation ◽  
Data Sets ◽  
Data Set ◽  
Topographic Features ◽  
Temperature And Precipitation ◽  
Simulated Precipitation

The regional climate model HIRHAM has been applied over the Asian continent to simulate the Indian monsoon circulation under present-day conditions. The model is driven at the lateral and lower boundaries by European reanalysis (ERA40) data for the period from 1958 to 2001. Simulations with a horizontal resolution of 50 km are carried out to analyze the regional monsoon patterns. The focus in this paper is on the validation of the long-term summer monsoon climatology and its variability concerning circulation, temperature, and precipitation. Additionally, the monsoonal behavior in simulations for wet and dry years has been investigated and compared against several observational data sets. The results successfully reproduce the observations due to a realistic reproduction of topographic features. The simulated precipitation shows a better agreement with a high-resolution gridded precipitation data set over the central land areas of India and in the higher elevated Tibetan and Himalayan regions than ERA40.

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 262 ◽  
Author(s):  
Coraline Wyard ◽  
Sébastien Doutreloup ◽  
Alexandre Belleflamme ◽  
Martin Wild ◽  
Xavier Fettweis
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Radiative Flux ◽  
Added Value ◽  
Historical Trends ◽  
The Mean

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

scholarly journals Summer drought in Switzerland 1981‒2020: Events, trends and drivers

2021 ◽  
Author(s):  
Simon C. Scherrer ◽  
Christoph Spirig ◽  
Martin Hirschi ◽  
Felix Maurer ◽  
Sven Kotlarski
Keyword(s):  
Regional Climate Model ◽  
Soil Water ◽  
Climate Model ◽  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Summer Drought ◽  
Temperature And Precipitation ◽  
Temperature Scaling

<p>The Alpine region has recently experienced several dry summers with negative impacts on the economy, society and ecology. Here, soil water, evapotranspiration and meteorological data from several observational and model-based data sources is used to assess events, trends and drivers of summer drought in Switzerland in the period 1981‒2020. 2003 and 2018 are identified as the driest summers followed by somewhat weaker drought conditions in 2020, 2015 and 2011. We find clear evidence for an increasing summer drying in Switzerland. The observed climatic water balance (-39.2 mm/decade) and 0-1 m soil water from reanalysis (ERA5-Land: -4.7 mm/decade; ERA5: -7.2 mm/decade) show a clear tendency towards summer drying with decreasing trends in most months. Increasing evapotranspiration (potential evapotranspiration: +21.0 mm/decade; ERA5-Land actual evapotranspiration: +15.1 mm/decade) is identified as important driver which scales excellently (+4 to +7%/K) with the observed strong warming of about 2°C. An insignificant decrease in precipitation further enhanced the tendency towards drier conditions. Most simulations of the EURO-CORDEX regional climate model ensemble underestimate the changes in summer drying. They underestimate both, the observed recent summer warming and the small decrease in precipitation. The changes in temperature and precipitation are negatively correlated, i.e. simulations with stronger warming tend to show (weak) decreases in precipitation. However, most simulations and the reanalysis overestimate the correlation between temperature and precipitation and the precipitation-temperature scaling on the interannual time scale. Our results emphasize that the analysis of the regional summer drought evolution and its drivers remains challenging especially with regional climate model data but considerable uncertainties also exist in reanalysis data sets.</p>

scholarly journals Model cascade from meteorological drivers to river flood hazard: flood-cascade v1.0

2021 ◽  
Vol 14 (8) ◽  
pp. 4865-4890
Author(s):  
Peter Uhe ◽  
Daniel Mitchell ◽  
Paul D. Bates ◽  
Nans Addor ◽  
Jeff Neal ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
River Flow ◽  
Climate Model ◽  
Climate Modeling ◽  
Flood Hazard ◽  
Spatial Scales ◽  
Computational Cost ◽  
Data Sets ◽  
Flood Inundation

Abstract. Riverine flood hazard is the consequence of meteorological drivers, primarily precipitation, hydrological processes and the interaction of floodwaters with the floodplain landscape. Modeling this can be particularly challenging because of the multiple steps and differing spatial scales involved in the varying processes. As the climate modeling community increases their focus on the risks associated with climate change, it is important to translate the meteorological drivers into relevant hazard estimates. This is especially important for the climate attribution and climate projection communities. Current climate change assessments of flood risk typically neglect key processes, and instead of explicitly modeling flood inundation, they commonly use precipitation or river flow as proxies for flood hazard. This is due to the complexity and uncertainties of model cascades and the computational cost of flood inundation modeling. Here, we lay out a clear methodology for taking meteorological drivers, e.g., from observations or climate models, through to high-resolution (∼90 m) river flooding (fluvial) hazards. Thus, this framework is designed to be an accessible, computationally efficient tool using freely available data to enable greater uptake of this type of modeling. The meteorological inputs (precipitation and air temperature) are transformed through a series of modeling steps to yield, in turn, surface runoff, river flow, and flood inundation. We explore uncertainties at different modeling steps. The flood inundation estimates can then be related to impacts felt at community and household levels to determine exposure and risks from flood events. The approach uses global data sets and thus can be applied anywhere in the world, but we use the Brahmaputra River in Bangladesh as a case study in order to demonstrate the necessary steps in our hazard framework. This framework is designed to be driven by meteorology from observational data sets or climate model output. In this study, only observations are used to drive the models, so climate changes are not assessed. However, by comparing current and future simulated climates, this framework can also be used to assess impacts of climate change.

scholarly journals A Comprehensive Assessment of Tropical Stratospheric Upwelling in Specified Dynamics CESM1.2.2 (WACCM)

2019 ◽  
Author(s):  
Nicholas A. Davis ◽  
Sean M. Davis ◽  
Robert W. Portmann ◽  
Eric Ray ◽  
Karen H. Rosenlof ◽  
...  
Keyword(s):  
Best Practices ◽  
Climate Models ◽  
Climate Model ◽  
Meridional Circulation ◽  
Trace Gas ◽  
Mean Meridional Circulation ◽  
Community Earth System Model ◽  
Free Running ◽  
The Mean ◽  
Wave Momentum

Abstract. Specified dynamics (SD) schemes relax the circulation in climate models toward a reference meteorology to simulate historical variability. These simulations are widely used to isolate the dynamical contributions to variability and trends in trace gas species. However, it is not clear if trends in the stratospheric overturning circulation are properly reproduced by SD schemes. This study assesses numerous SD schemes and modeling choices in the Community Earth System Model (CESM) Whole Atmosphere Chemistry Climate Model (WACCM) to determine a set of best practices for reproducing interannual variability and trends in tropical stratospheric upwelling estimated by reanalyses. Nudging toward the reanalysis meteorology as is typically done in SD simulations expectedly changes the model’s mean upwelling compared to its free-running state, but does not accurately reproduce upwelling trends present in the underlying reanalysis. In contrast, nudging to anomalies from the climatological winds or from the zonal mean winds and temperatures preserves WACCM’s climatology and better reproduces trends in stratospheric upwelling. An SD scheme’s performance in simulating the acceleration of the shallow branch of the mean meridional circulation from 1980–2017 hinges on its ability to simulate the downward shift of subtropical lower stratospheric wave momentum forcing. Key to this is not nudging the zonal-mean temperature field. Gravity wave momentum forcing, which drives a substantial fraction of the upwelling in WACCM, cannot be constrained by nudging and presents an upper-limit on the performance of these schemes.

Can climate models capture the high amplitudes circumglobal waves and their surface imprints?  

2021 ◽  
Author(s):  
Fei Luo ◽  
Kai Kornhuber ◽  
Frank Selten ◽  
Dim Coumou
Keyword(s):  
Soil Moisture ◽  
Climate Models ◽  
Phase Locking ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
Circulation Types ◽  
Temperature And Precipitation ◽  
Wave Patterns ◽  
Precipitation Anomalies ◽  
June July

<p>Pronounced circumglobal waves can trigger and maintain persistent summer weather conditions by remaining in their preferred phase-locked positions for several weeks in a row. This phenomenon, especially important for wave numbers 5 and 7, has been observed in recent years, but it is unclear whether climate models can reproduce circulation types and their surface imprints.</p><p>Here we assess three climate models (EC-Earth3, CESM1.2, and MIROC5)  for their representation of amplified circumglobal waves and associated surface imprints in summer (June, July and August) over 1979-2016. ERA5 reanalysis data is used as reference to assess the models’ performance. We run a series of modeling experiments to understand the source of biases in the climate models: free interactive atmosphere and soil moisture runs (AISI), atmospheric nudged runs (AFSI), soil moisture prescribed runs (AISF), and both atmosphere and soil moisture nudged experiments (AFSF).</p><p>We show that all models reasonably well reproduce the climatological wave spectra. Further, both wave 5 and wave 7 are found to exhibit phase-locking behaviors across all models, resulting in similar wave patterns across the hemisphere as compared to reanalysis. The surface imprints are observed in the models as well, but depending on the model, the results vary in strength. We also found the biases in surface temperature and precipitation anomalies mainly come from the atmospheric circulation in the models as these biases reduced considerably from AISI runs to AFSI and AFSF runs where upper atmosphere levels were nudged. Nudging soil moisture also minimizes some biases in the models but not as obvious as nudging the atmosphere. </p><div> <div> <div> </div> </div> </div>

Challenges for Diadromous Fishes in a Dynamic Global Environment

2009 ◽  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Generalized Additive Models ◽  
Habitat Characteristics ◽  
Explanatory Variables ◽  
Temperature And Precipitation ◽  
Management Plans ◽  
The Face ◽  
Uncertain Future ◽  
Diadromous Species

<em>Abstract</em>.-Climate change can have an effect on species distributions. The 1900 distribution and potential future distribution of diadromous fish in Europe, North Africa, and the Middle East were explored using generalized additive models (GAMs) and selected habitat characteristics of 196 basins. Robust presence-absence models were built for 20 of the 28 diadromous species in the study area using longitude, annual temperature, drainage surface area, annual precipitation, and source elevation as explanatory variables. Inspection of the relationship between each variable and species presence-absence revealed that the GAMs were generally interpretable and plausible. Given the predicted rise in annual temperature in climate models ranging between 1°C and 7°C by 2100, the fish species were classified according to those losing suitable basins, those gaining suitable basins, and those showing little or no change. It was found that the climate envelopes based on temperature and precipitation for diadromous species would, in general, be shifted farther northeastwards by 2100, and these shifting ranges were comparable with those assessed in other studies. The uncertain future of some species was highlighted, and it was concluded that conservation policy and management plans will need to be revised in the face of climate change.

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