A global evaluation of streamflow drought characteristics

How drought is characterised depends on the purpose and region of the study and the available data. In case of regional applications or global comparison a standardisation of the methodology to characterise drought is preferable. In this study the threshold level method in combination with three common pooling procedures is applied to daily streamflow series from a wide range of hydrological regimes. Drought deficit characteristics, such as drought duration and deficit volume, are derived, and the methods are evaluated for their applicability for regional studies. Three different pooling procedures are evaluated: the moving-average procedure (MA-procedure), the inter-event time method (IT-method), and the sequent peak algorithm (SPA). The MA-procedure proved to be a flexible approach for the different series, and its parameter, the averaging interval, can easily be optimised for each stream. However, it modifies the discharge series and might introduce dependency between drought events. For the IT-method it is more difficult to find an optimal value for its parameter, the length of the excess period, in particular for flashy streams. The SPA can only be recommended as pooling procedure for the selection of annual maximum series of deficit characteristics and for very low threshold levels to ensure that events occurring shortly after major events are recognized. Furthermore, a frequency analysis of deficit volume and duration is conducted based on partial duration series of drought events. According to extreme value theory, excesses over a certain limit are Generalized Pareto (GP) distributed. It was found that this model indeed performed better than or equally to other distribution models. In general, the GP-model could be used for streams of all regime types. However, for intermittent streams, zero-flow periods should be treated as censored data. For catchments with frost during the winter season, summer and winter droughts have to be analysed separately

Localization of ampa-selective excitatory amino acid receptor subunits in identified populations of striatal neurons

Two-color immunofluorescence histochemistry and immunohistochemistry in combination with retrograde tract-tracing techniques were used to examine the relationship of [alpha]-amino-3-hydroxy-5-methyl-4-isoxazole proprionic acid (AMPA)-selective glutamate receptor subunits (GluR1, GluR2/3/4c and GluR4) to identified populations of striatal projection neurons and interneurons. The majority of striatonigral and striatopallidal neurons were double-labeled for GluR2/3/4c. These findings were confirmed using calbindin to label matrix projection neurons. In contrast, immunostaining of the GluR1 subunit was not observed to co-localize with any striatal projection neurons. Striatal interneurons immunostained for parvalbumin were also labeled by antibodies directed against the GluRl subunit. Approximately 50% of parvalbumin neurons also contained GluR2/3/4c. Somatostatin immunoreactivity did not co-localize with either the GluR1 or GluR2/3/4c subunits. GluR4-immunoreactive neurons were not observed in striatum.This study demonstrates that AMPA-selective glutamate receptors are differentially localized on subpopulations of striatal neurons and interneurons. These findings suggest that discrete striatal neuron populations may express different AMPA receptor subunit combinations which may account for their functional specificity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31419/1/0000336.pd

COST 733 - WG4: Applications of weather type classification

The main objective of the COST Action 733 is to achieve a general numerical method for assessing, comparing and classifying typical weather situations in the European regions. To accomplish this goal, different workgroups are established, each with their specific aims: WG1: Existing methods and applications (finished); WG2: Implementation and development of weather types classification methods; WG3: Comparison of selected weather types classifications; WG4: Testing methods for various applications. The main task of Workgroup 4 (WG4) in COST 733 implies the testing of the selected weather type methods for various classifications. In more detail, WG4 focuses on the following topics:• Selection of dedicated applications (using results from WG1), • Performance of the selected applications using available weather types provided by WG2, • Intercomparison of the application results as a results of different methods • Final assessment of the results and uncertainties, • Presentation and release of results to the other WGs and external interested • Recommend specifications for a new (common) method WG2 Introduction In order to address these specific aims, various applications are selected and WG4 is divided in subgroups accordingly: 1.Air quality 2. Hydrology (& Climatological mapping) 3. Forest fires 4. Climate change and variability 5. Risks and hazards Simultaneously, the special attention is paid to the several wide topics concerning some other COST Actions such as: phenology (COST725), biometeorology (COST730), agriculture (COST 734) and mesoscale modelling and air pollution (COST728). Sub-groups are established to find advantages and disadvantages of different classification methods for different applications. Focus is given to data requirements, spatial and temporal scale, domain area, specifi

Streamflow forecast sensitivity to air temperature forecast calibration for 139 Norwegian catchments

In this study, we used meteorological ensemble forecasts as input to hydrological models to quantify the uncertainty in forecasted streamflow, with a particular focus on the effect of temperature forecast calibration on the streamflow ensemble forecast skill. In catchments with seasonal snow cover, snowmelt is an important flood-generating process. Hence, high-quality air temperature data are important to accurately forecast streamflows. The sensitivity of streamflow ensemble forecasts to the calibration of temperature ensemble forecasts was investigated using ensemble forecasts of temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) covering a period of nearly 3 years, from 1 March 2013 to 31 December 2015. To improve the skill and reduce biases of the temperature ensembles, the Norwegian Meteorological Institute (MET Norway) provided parameters for ensemble calibration, derived using a standard quantile mapping method where HIRLAM, a high-resolution regional weather prediction model, was used as reference. A lumped HBV (Hydrologiska Byråns Vattenbalansavdelning) model, distributed on 10 elevation zones, was used to estimate the streamflow. The results show that temperature ensemble calibration affected both temperature and streamflow forecast skill, but differently depending on season and region. We found a close to 1:1 relationship between temperature and streamflow skill change for the spring season, whereas for autumn and winter large temperature skill improvements were not reflected in the streamflow forecasts to the same degree. This can be explained by streamflow being less affected by subzero temperature improvements, which accounted for the biggest temperature biases and corrections during autumn and winter. The skill differs between regions. In particular, there is a cold bias in the forecasted temperature during autumn and winter along the coast, enabling a large improvement by calibration. The forecast skill was partly related to elevation differences and catchment area. Overall, it is evident that temperature forecasts are important for streamflow forecasts in climates with seasonal snow cover.</p

Snow-vegetation-atmosphere interactions in alpine tundra

The interannual variability of snow cover in alpine areas is increasing, which may affect the tightly coupled cycles of carbon and water through snow-vegetation-atmosphere interactions across a range of spatio-temporal scales. To explore the role of snow cover for the land-atmosphere exchange of CO2 and water vapor in alpine tundra ecosystems, we combined three years (2019&ndash;2021) of continuous eddy covariance flux measurements of net ecosystem exchange of CO2 (NEE) and evapotranspiration (ET) from the Finse site in alpine Norway (1210 m a.s.l.) with a ground-based ecosystem-type classification and satellite imagery from Sentinel-2, Landsat 8, and MODIS. While the snow conditions in 2019 and 2021 can be described as site-typical, 2020 features an extreme snow accumulation associated with a strong negative phase of the Scandinavian Pattern of the synoptic atmospheric circulation during spring. This extreme snow accumulation caused a one-month delay in melt-out date, which falls on the 92nd-percentile in the distribution of yearly melt-out dates in the period 2001&ndash;2021. The melt-out dates follow a consistent fine-scale spatial relationship with ecosystem types across years. Mountain and lichen heathlands melt out more heterogeneously than fens and flood plains, while late snowbeds melt out up to one month later than the other ecosystem types. While the summertime average Normalized Difference Vegetation Index (NDVI) was reduced considerably during the extreme snow year 2020, it reached the same maximum as in the other years for all but one the ecosystem type (late snowbeds), indicating that the delayed onset of vegetation growth is compensated to the same maximum productivity. Eddy covariance estimates of NEE and ET are gap-filled separately for two wind sectors using a random forest regression model to account for complex and nonlinear ecohydrological interactions. While the two wind sectors differ markedly in vegetation composition and flux magnitudes, their flux response is controlled by the same drivers as estimated by the predictor importance of the random forest model as well as the high correlation of flux magnitudes (correlation coefficient r = 0.92 for NEE and r = 0.89 for ET) between both areas. The one-month delay of the start of the snow-free season in 2020 reduced the total annual ET by 50 % compared to 2019 and 2021, and reduced the growing season carbon assimilation to turn the ecosystem from a moderate annual carbon sink (&minus;31 to &minus;6 gC m&minus;2 yr&minus;1) to a source (34 to 20 gC m&minus;2 yr&minus;1). These results underpin the strong dependence of ecosystem structure and functioning on snow dynamics, whose anomalies can result in important ecological extreme events for alpine ecosystems.</p

Simplifying the clinical classification of polymerase gamma (POLG) disease based on age of onset; studies using a cohort of 155 cases

Background: Variants in POLG are one of the most common causes of inherited mitochondrial disease. Phenotypic classification of POLG disease has evolved haphazardly making it complicated and difficult to implement in everyday clinical practise. The aim of our study was to simplify the classification and facilitate better clinical recognition. / Methods: A multinational, retrospective study using data from 155 patients with POLG variants recruited from seven European countries. / Results: We describe the spectrum of clinical features associated with POLG variants in the largest known cohort of patients. While clinical features clearly form a continuum, stratifying patients simply according to age of onset—onset prior to age 12 years; onset between 12 and 40 years and onset after the age of 40 years, permitted us to identify clear phenotypic and prognostic differences. Prior to 12 years of age, liver involvement (87%), seizures (84%), and feeding difficulties (84%) were the major features. For those with onset between 12 and 40 years, ataxia (90%), peripheral neuropathy (84%), and seizures (71%) predominated, while for those with onset over 40 years, ptosis (95%), progressive external ophthalmoplegia (89%), and ataxia (58%) were the major clinical features. The earlier the onset the worse the prognosis. Patients with epilepsy and those with compound heterozygous variants carried significantly worse prognosis. / Conclusion: Based on our data, we propose a simplified POLG disease classification, which can be used to guide diagnostic investigations and predict disease course

Natural and human influences on the link between meteorological and hydrological drought indices for a large set of catchments in the contiguous United States

Precipitation‐based drought indices are most commonly used in drought monitoring and early warning systems whereas impacts of drought are often related to other domains of the hydrological cycle such as streamflow. Precipitation droughts do not always coincide with streamflow droughts, as the propagation from precipitation to streamflow is affected by climate, catchment properties and human influences. For monitoring in ungauged catchments it is the question to what extent drought indices solely based on precipitation or other (more recently developed) meteorological drought indices that include evaporation or snowmelt, have a stronger correlation with streamflow and whether this correlation is weaker in catchments where streamflow is altered by human influences. Results of a correlation exercise between various meteorological drought indices and streamflow showed that the strongest correlation was often found for meteorological drought indices that include evaporation (especially in drier climates) or snow processes (especially in colder climates). Most catchments with an indicated presence of human influences showed a maximum correlation between meteorological drought indices and streamflow that was comparable in strength to the same correlation for catchments with near‐natural flow. However, up to 15% of catchments with human‐influenced streamflow records show weaker correlations. Drought indices derived from these influenced records with a weaker correlation do not necessarily correspond to reported drought impacts. In conclusion, knowing which meteorological drought index has the strongest correlation with streamflow in different climate zones has the potential of improving large‐scale drought monitoring and early warning systems in ungauged areas or regions that lack real‐time streamflow availability

The impact of gender, puberty, and pregnancy in patients with POLG disease

OBJECTIVE: To study the impact of gender, puberty, and pregnancy on the expression of POLG disease, one of the most common mitochondrial diseases known. METHODS: Clinical, laboratory, and genetic data were collected retrospectively from 155 patients with genetically confirmed POLG disease recruited from seven European countries. We used the available data to study the impact of gender, puberty, and pregnancy on disease onset and deterioration. RESULTS: We found that disease onset early in life was common in both sexes but there was also a second peak in females around the time of puberty. Further, pregnancy had a negative impact with 10 of 14 women (71%) experiencing disease onset or deterioration during pregnancy. INTERPRETATION: Gender clearly influences the expression of POLG disease. While onset very early in life was common in both males and females, puberty in females appeared associated both with disease onset and increased disease activity. Further, both disease onset and deterioration, including seizure aggravation and status epilepticus, appeared to be associated with pregnancy. Thus, whereas disease activity appears maximal early in life with no subsequent peaks in males, both menarche and pregnancy appear associated with disease onset or worsening in females. This suggests that hormonal changes may be a modulating factor