scholarly journals Quantifying parameter uncertainty in a large-scale glacier evolution model using Bayesian inference: application to High Mountain Asia

2020 ◽  
Vol 66 (256) ◽  
pp. 175-187 ◽  
Author(s):  
David R. Rounce ◽  
Tushar Khurana ◽  
Margaret B. Short ◽  
Regine Hock ◽  
David E. Shean ◽  
...  
Keyword(s):  
Mass Balance ◽  
Parameter Uncertainty ◽  
Large Scale ◽  
Evolution Model ◽  
Model Parameters ◽  
High Mountain ◽  
Climate Data ◽  
Temperature And Precipitation ◽  
Model Parameter Uncertainty ◽  
Geodetic Mass Balance

AbstractThe response of glaciers to climate change has major implications for sea-level change and water resources around the globe. Large-scale glacier evolution models are used to project glacier runoff and mass loss, but are constrained by limited observations, which result in models being over-parameterized. Recent systematic geodetic mass-balance observations provide an opportunity to improve the calibration of glacier evolution models. In this study, we develop a calibration scheme for a glacier evolution model using a Bayesian inverse model and geodetic mass-balance observations, which enable us to quantify model parameter uncertainty. The Bayesian model is applied to each glacier in High Mountain Asia using Markov chain Monte Carlo methods. After 10,000 steps, the chains generate a sufficient number of independent samples to estimate the properties of the model parameters from the joint posterior distribution. Their spatial distribution shows a clear orographic effect indicating the resolution of climate data is too coarse to resolve temperature and precipitation at high altitudes. Given the glacier evolution model is over-parameterized, particular attention is given to identifiability and the need for future work to integrate additional observations in order to better constrain the plausible sets of model parameters.

scholarly journals Homogeneity Test and Correction of Daily Temperature and Precipitation Data (1978–2015) in North China

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Lingling Shen ◽  
Li Lu ◽  
Tianjie Hu ◽  
Runsheng Lin ◽  
Ji Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
North China ◽  
Maximum Temperature ◽  
Homogeneity Test ◽  
Climate Data ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Daily Data ◽  
Before And After ◽  
Annual Average Temperature

Homogeneity of climate data is the basis for quantitative assessment of climate change. By using the MASH method, this work examined and corrected the homogeneity of the daily data including average, minimum, and maximum temperature and precipitation during 1978–2015 from 404/397 national meteorological stations in North China. Based on the meteorological station metadata, the results are analyzed and the differences before and after homogenization are compared. The results show that breakpoints are present pervasively in these temperature data. Most of them appeared after 2000. The stations with a host of breakpoints are mainly located in Beijing, Tianjin, and Hebei Province, where meteorological stations are densely distributed. The numbers of breakpoints in the daily precipitation series in North China during 1978–2015 also culminated in 2000. The reason for these breakpoints, called inhomogeneity, may be the large-scale replacement of meteorological instruments after 2000. After correction by the MASH method, the annual average temperature and minimum temperature decrease by 0.04°C and 0.06°C, respectively, while the maximum temperature increases by 0.01°C. The annual precipitation declines by 0.96 mm. The overall trends of temperature change before and after the correction are largely consistent, while the homogeneity of individual stations is significantly improved. Besides, due to the correction, the majority series of the precipitation are reduced and the correction amplitude is relatively large. During 1978–2015, the temperature in North China shows a rise trend, while the precipitation tends to decrease.

Impact of the choice of surface mass balance models and their calibration on large-scale glacier change projections

2021 ◽  
Author(s):  
Lilian Schuster ◽  
David Rounce ◽  
Fabien Maussion
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Model Complexity ◽  
Model Parameters ◽  
Glacier Change ◽  
Surface Mass Balance ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Mass Balance Models ◽  
Intercomparison Study

<p>A recent large model intercomparison study (GlacierMIP) showed that differences between the glacier models is a dominant source of uncertainty for future glacier change projections, in particular in the first half of the century.  Each glacier model has their own unique set of process representations and climate forcing methodology, which makes it impossible to determine the model components that contribute most to the projection uncertainty. This study aims to improve our understanding of the sources of large scale glacier model uncertainty using the Open Global Glacier Model (OGGM), focussing on the surface mass balance (SMB) in a first step. We calibrate and run a set of interchangeable SMB model parameterizations (e.g. monthly vs. daily, constant vs. variable lapse rates, albedo, snowpack evolution and refreezing) under controlled boundary conditions. Based on ensemble approaches, we explore the influence of (i) the parameter calibration strategy and (ii) SMB model complexity on regional to global glacier change. These uncertainties are then put in relation to a qualitative selection of other model design choices, such as the forcing climate dataset and ice dynamics model parameters. </p>

Predicting Spring Tornado Activity in the Central Great Plains by 1 March

2014 ◽  
Vol 142 (1) ◽  
pp. 259-267 ◽  
Author(s):  
James B. Elsner ◽  
Holly M. Widen
Keyword(s):  
Great Plains ◽  
Large Scale ◽  
Negative Binomial ◽  
Gulf Of Alaska ◽  
Model Parameters ◽  
Climate Data ◽  
Convective Storms ◽  
Bayesian Formulation ◽  
Out Of Sample ◽  
Western Caribbean

Abstract The authors illustrate a statistical model for predicting tornado activity in the central Great Plains by 1 March. The model predicts the number of tornado reports during April–June using February sea surface temperature (SST) data from the Gulf of Alaska (GAK) and the western Caribbean Sea (WCA). The model uses a Bayesian formulation where the likelihood on the counts is a negative binomial distribution and where the nonstationarity in tornado reporting is included as a trend term plus first-order autocorrelation. Posterior densities for the model parameters are generated using the method of integrated nested Laplacian approximation (INLA). The model yields a 51% increase in the number of tornado reports per degree Celsius increase in SST over the WCA and a 15% decrease in the number of reports per degree Celsius increase in SST over the GAK. These significant relationships are broadly consistent with a physical understanding of large-scale atmospheric patterns conducive to severe convective storms across the Great Plains. The SST covariates explain 11% of the out-of-sample variability in observed F1–F5 tornado reports. The paper demonstrates the utility of INLA for fitting Bayesian models to tornado climate data.

Understanding monsoon controls on the energy- and mass-balance of glaciers in High Mountain Asia

2020 ◽  
Author(s):  
Stefan Fugger ◽  
Evan Miles ◽  
Michael McCarthy ◽  
Catriona Fyffe ◽  
Marin Kneib ◽  
...  
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Balance Model ◽  
Large Temperature ◽  
High Mountain ◽  
Glacier Surface ◽  
Weather Patterns ◽  
Mass Balance Models ◽  
High Precipitation ◽  
Study Sites

<p>The Indian Summer Monsoon (ISM) shapes the melt and accumulation patterns of glaciers in large parts of High Mountain Asia (HMA) in complex ways due to the interaction of persistent cloud-cover, large temperature amplitudes, high atmospheric water content and high precipitation rates. While the ISM dominates in the southern and eastern regions, it progressively loses influence westward towards the Karakoram, where the influence of westerlies is predominant. Previous applications of energy- and mass-balance models for glaciers in HMA have been limited to single study sites (in Khumbu, Langtang and Parlung) and a few attempted to link model results to large-scale weather patterns. While these studies have helped to understand the energy- and mass-balance of glaciers in HMA under specific local climates, a regional perspective is still missing. In this study, we use a full energy- and mass-balance model together  with eight on-glacier AWS datasets around HMA to investigate how ISM conditions influence glacier-surface energy and mass balance. In particular, we look at how debris-covered and debris-free glaciers respond differently to the ISM, validating our results against independent in-situ measurements. This work is fundamental to the development of parameterizations of glacier melt for long-term hydrological studies and to the understanding of the present and future HMA cryosphere and water budget evolution.</p>

scholarly journals Sensitivity to climate change of the mass balance of glaciers in southern Norway

1993 ◽  
Vol 39 (133) ◽  
pp. 656-665 ◽  
Author(s):  
Tron Laumann ◽  
Niels Reeh
Keyword(s):  
Mass Balance ◽  
Atlantic Coast ◽  
Elevation Gradient ◽  
Greenland Ice Sheet ◽  
Climatic Conditions ◽  
Model Parameters ◽  
Average Mass ◽  
Degree Day ◽  
Temperature And Precipitation ◽  
Southern Norway

Abstract A degree-day model developed for parameterizing melt rates on the Greenland ice sheet is adapted to the climatic conditions on glaciers in southern Norway. The model is calibrated by means of observed average mass-balance-elevation relationships (1963–90) for three glaciers in a west-east transect in southern Norway and 30 year normals (1961–90) of temperature and precipitation observed at nearby climate stations. The calibration gives a surprisingly small variation of the model parameters (degree-day factors for snow-and ice-melt, and precipitation-elevation gradient) from one glacier to another. The derived values of the parameters are used to estimate the change of the mass-balance-elevation relationship for different climatic scenarios. The study indicates that a low-lying glacier in the maritime, high-precipitation environment near the Atlantic coast is more sensitive to both temperature and precipitation changes than the high elevated glaciers in the dry, more continental climate farther away from the coast. However, all of the glaciers studied will lose mass in a warmer climate, unless the warming is accompanied by a dramatic increase in the precipitation of 25–40% deg−1 warming.

scholarly journals Online dynamical downscaling of temperature and precipitation within the <i>i</i>LOVECLIM model (version 1.1)

2018 ◽  
Vol 11 (1) ◽  
pp. 453-466
Author(s):  
Aurélien Quiquet ◽  
Didier M. Roche ◽  
Christophe Dumas ◽  
Didier Paillard
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Atmospheric Model ◽  
Scale Model ◽  
Model Parameters ◽  
Temperature And Precipitation ◽  
Large Scale Model

Abstract. This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km  ×  40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.

scholarly journals Does the High Elevation Climate along Mt. Everest can be Represented by Lower Elevation Stations?

2021 ◽  
Vol 26 (2) ◽  
pp. 99-109
Author(s):  
Binod Dawadi ◽  
Shankar Sharma ◽  
Kalpana Hamal ◽  
Nitesh Khadka ◽  
Yam Prasad Dhital ◽  
...  
Keyword(s):  
Climate Change ◽  
Climatic Factors ◽  
Monsoon Season ◽  
High Elevation ◽  
High Mountain ◽  
Climate Data ◽  
Southern Slope ◽  
Mountain Areas ◽  
Temperature And Precipitation ◽  
Lower Elevation

Climate change studies of the high mountain areas of the central Himalayan region are mostly represented by the meteorological stations of the lower elevation. Therefore, to validate the climatic linkages, daily observational climate data from five automated weather stations (AWS) at elevations ranging from 2660 m to 5600 m on the southern slope of Mt. Everest were examined. Despite variations in the means and distribution of daily, 5-day, 10-day, and monthly temperature and precipitation between stations located at a higher elevation and their corresponding lower elevation, temperature records in the different elevations are highly correlated. In contrast, the precipitation data shows a comparatively weaker correlation. The slopes of the regression model (0.82–1.13) with (R2>0.74) for higher altitude (5050 m and 5600 m) throughout the year, 0.83–1.12 (R2>0.68) except late monsoon season for the station at 4260 m and 5050 m asl indicated the similar variability of the temperature between those stations. Similarly, Namche (3570 m) temperature changes by 0.81–1.32°C per degree change in corresponding lower elevation Lukla station (2660 m), except for monsoon season. However, inconsistent variation was observed between the station with a large altitudinal difference (2940 m) at Lukla and Kala Patthar (5600 m). In general, climate records from corresponding lower elevation can be used to quantitatively assess climatic information of the high elevation areas on the southern slope of Mt. Everest. However, corrections are necessary when absolute values of climatic factors are considered, especially in snow cover and snow-free areas. This study will be beneficial for understanding the high-altitude climate change and impact studies.

scholarly journals Investigating spatiotemporal patterns of snowline altitude at the end of melting season in High Mountain Asia, using cloud-free MODIS snow cover product, 2001–2016

2019 ◽  
Author(s):  
Zhiguang Tang ◽  
Xiaoru Wang ◽  
Jian Wang ◽  
Xin Wang ◽  
Junfeng Wei
Keyword(s):  
Mass Balance ◽  
Snow Cover ◽  
Large Scale ◽  
Tien Shan ◽  
Spatiotemporal Pattern ◽  
High Mountain ◽  
Mountainous Area ◽  
Polar Regions ◽  
Equilibrium Line Altitude ◽  
Melting Season

Abstract. The snowline altitude at the end of melting season (SLA-EMS) can be used as an indicator of the equilibrium line altitude (ELA) and therefore for the annual mass balance of glaciers in certain conditions. High Mountain Asia (HMA) hosts the largest glacier and perennial snow cover concentration outside the polar regions, but the spatiotemporal pattern of SLA-EMS under climate change is poorly understood in there. Here, we develop a method for estimating SLA-EMS over large-scale area by using the cloud-removed MODIS fractional snow cover data, and investigate the spatiotemporal characteristics and trends of SLA-EMS during 2001–2016 over the HMA. The possible linkage between the SLA-EMS and temperature and precipitation changes over the HMA is also investigated. The results are as follows: (1) There are good linear regression relationships (R = −0.66) between the extracted grid (30 km) SLA-EMS and glaciers annual mass balance over the HMA. (2) Generally, the SLA-EMS in the HMA decreases with increase of latitude. And due to the mass elevation effect, it decreases from the high altitude region of Himalayas and inner Tibet to surrounding low mountainous area. (3) The SLA-EMS of HMA generally shows a rising trend in the recent years (2001–2016). In total, 75.3 % (24.2 % with a significant increase) and 16.1 % (less than 1 % with a significant decrease) of the study area show increasing and decreasing trends in SLA-EMS, respectively. The SLA-EMS significant increases in Tien Shan, Inner Tibet, south and east Tibet, east Himalaya and Hengduan Shan. (4) Temperature (especially the summer temperature) trends to be the dominant climatic factor affecting the variations of SLA-EMS over the HMA. Under the background of the generally losing glaciers mass in HMA, if the SLA-EMS continues to rise as a result of global warming, it will accelerate the negative mass balances of the glaciers. This study is an important step towards reconstruction the time series of glacier annual mass balance using SLA-EMS datasets at the scale of HMA to better document the relationships between climate and glaciers.

scholarly journals Sensitivity to climate change of the mass balance of glaciers in southern Norway

1993 ◽  
Vol 39 (133) ◽  
pp. 656-665 ◽  
Author(s):  
Tron Laumann ◽  
Niels Reeh
Keyword(s):  
Mass Balance ◽  
Atlantic Coast ◽  
Elevation Gradient ◽  
Greenland Ice Sheet ◽  
Climatic Conditions ◽  
Model Parameters ◽  
Average Mass ◽  
Degree Day ◽  
Temperature And Precipitation ◽  
Southern Norway

AbstractA degree-day model developed for parameterizing melt rates on the Greenland ice sheet is adapted to the climatic conditions on glaciers in southern Norway. The model is calibrated by means of observed average mass-balance-elevation relationships (1963–90) for three glaciers in a west-east transect in southern Norway and 30 year normals (1961–90) of temperature and precipitation observed at nearby climate stations. The calibration gives a surprisingly small variation of the model parameters (degree-day factors for snow-and ice-melt, and precipitation-elevation gradient) from one glacier to another. The derived values of the parameters are used to estimate the change of the mass-balance-elevation relationship for different climatic scenarios. The study indicates that a low-lying glacier in the maritime, high-precipitation environment near the Atlantic coast is more sensitive to both temperature and precipitation changes than the high elevated glaciers in the dry, more continental climate farther away from the coast. However, all of the glaciers studied will lose mass in a warmer climate, unless the warming is accompanied by a dramatic increase in the precipitation of 25–40% deg−1 warming.

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