Climate projections for glacier change modelling over the Himalayas.

Glaciers are of key importance to freshwater supplies in the Himalayan region. Their growth or decline is among other factors determined by an interaction of 2-m air temperature (TAS) and precipitation rate (PR) and thereof derived positive degree days (PDD) and snow and ice accumulation (SAC). To investigate determining factors in climate projections, we use a model ensemble consisting of 36 CMIP5 general circulation models (GCMs) and 13 regional climate models (RCMs) of two Asian CORDEX domains for two different representative concentration pathways (RCP4.5 and RCP8.5). First, we downsize the ensemble in respect to the models' ability to correctly reproduce dominant circulation patterns (i.e., the Indian summer monsoon [ISM] and western disturbances [WDs]) as well as elevation-dependent trend signals in winter. Within this evaluation, a newly produced data set for the Indus, Ganges and Brahmaputra catchments is used as observational data. The reanalyses WFDEI, ERA-Interim, NCEP/NCAR and JRA-55 are used to further account for observational uncertainty. In a next step, remaining TAS and PR data are bias corrected applying a new bias adjustment method, scale distribution mapping, and subsequently PDD and SAC computed. Finally, we identify and quantify projected climate change effects. Until the end of the century, the ensemble indicates a rise of PDD, especially during summer and for lower altitudes. Also TAS is rising, though the highest increases are shown for higher altitudes and between December and April (DJFMA). PRs connected to the ISM are projected to robustly increase, while signals for PR changes during DJFMA show a higher level of uncertainty and spatial heterogeneity. However, a robust decline in solid precipitation is projected over our research domain, with the exception of a small area in the high mountain Indus catchment where no clear signal emerges.

Selecting climate simulations for impact studies based on multivariate patterns of climate change.

In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.

Investigation of climate change impact on water resources for an Alpine basin in northern Italy: implications for evapotranspiration modeling complexity.

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.

Quantitative assessment of patellar cartilage volume and thickness at 3.0 tesla comparing a 3D-fast low angle shot versus a 3D-true fast imaging with steady-state precession sequence for reproducibility.

OBJECTIVES: We sought to compare patellar cartilage volume and thickness measurement between 3D-FLASH and 3D-True fast imaging with steady-state precession (FISP) image data at 3.0 T. MATERIALS AND METHODS: One knee each of 6 healthy adults was examined by axial magnetic resonance imaging (MRI) performed with a 3D-fast flow angle shot (FLASH) water-excitation sequence and a 3D-TrueFISP water-excitation sequence (spatial resolution 0.31 x 0.31 x 1.5 mm3). Patellar cartilage volume and mean/maximum thickness were calculated. Intraindividual/average reproducibility and interindividual variability were determined from 3 consecutive data sets acquired for each volunteer and sequence. RESULTS: Patellar cartilage volume and thickness as well as reproducibility was slightly but not significantly lower for the 3D-TrueFISP data than for the 3D-FLASH data (volume: 3.4-6.3 mL (3D-FLASH)/3.1-6.0 mL (3D-TrueFISP), average reproducibility 1.8% (3D-FLASH)/4.4% (3D-TrueFISP); mean thickness: 2.1-2.8 mm (3D-FLASH)/1.9-2.6 mm (3D-TrueFISP), average reproducibility 2.8% (3D-FLASH)/3.8% (3D-TrueFISP); maximum thickness: 4.7-6.6 mm (3D-FLASH)/4.5-6.2 mm (3D-TrueFISP), average reproducibility 2.6% (3D-FLASH)/4.1% (3D-TrueFISP)). Interindividual variability was comparable for both sequence techniques. CONCLUSION: At 3.0 T, the 3D-FLASH sequence showed tendency to be slightly superior to the 3D-TrueFISP sequence considering robust and valid assessment of quantitative cartilage parameters in young healthy adults, although there was found no significant statistical difference between both imaging techniques. However, in patients suffering from osteoarthritis (OA), the 3D-TrueFISP sequence might prove advantageous for monitoring of disease progression and evaluation of therapy success, particularly because the substantially higher signal to noise ratio/contrast to noise ratio values might allow for higher spatial resolution and hence for improvement of the accuracy of segmentation process especially at the articular surface.

T2 quantitation of human articular cartilage in a clinical setting at 1.5 T: implementation and testing of four multiecho pulse sequence designs for validity.

RATIONALE AND OBJECTIVES: Evaluation of the T2 relaxation time of articular cartilage holds great potential for quantitative assessment of internal changes of the cartilage matrix. The purpose of the present study was to assess the validity of multiecho-based cartilage T2 quantitation in a clinical MRI setting at 1.5 T. METHODS: Four multisection multiecho sequence variants dedicated for quantitative T2 mapping of human articular cartilage were implemented on a 1.5 T whole-body imager and tested for accuracy in CuSO4-agarose gel phantoms and human patellar cartilage. Sequence design was varied to minimize errors in T2 quantitation due to stimulated echoes. RESULTS: As compared with single spin-echo experiments, the apparent T2 values calculated from the multiecho sequence variants showed mean deviations ranging from +26% to -32% (phantoms) and from +42% to -18% (cartilage). The patellar cartilage T2 covered a range from about 25 milliseconds to 55 milliseconds, with longer T2 values observed in the more superficial layers. In cartilage, best results were obtained from the sequence design using improved section profiles and a spoiler gradient scheme for suppression of stimulated echoes. CONCLUSIONS: Our results revealed a clear dependence of apparent T2 relaxation times on the pulse sequence design, emphasizing that the "true" T2 is hard to find. In addition, the effect on the apparent T2 values resulting from the specific modification of any sequence variant varied according to the respective tissue's properties. Therefore, the acquisition technique in conjunction with the specific tissue on which T2 mapping is performed need to be reported in detail and should kept consistent to allow large-scale comparisons and monitoring of treatment strategies, e.g., in osteoarthritis.