Assessment of subseasonal-to-seasonal (S2S) ensemble extreme precipitation forecast skill over Europe

Heavy precipitation can lead to floods and landslides, resulting in widespread damage and significant casualties. Some of its impacts can be mitigated if reliable forecasts and warnings are available. Of particular interest is the subseasonal-to-seasonal (S2S) prediction timescale. The S2S prediction timescale has received increasing attention in the research community because of its importance for many sectors. However, very few forecast skill assessments of precipitation extremes in S2S forecast data have been conducted. The goal of this article is to assess the forecast skill of rare events, here extreme precipitation, in S2S forecasts, using a metric specifically designed for extremes. We verify extreme precipitation events over Europe in the S2S forecast model from the European Centre for Medium-Range Weather Forecasts. The verification is conducted against ERA5 reanalysis precipitation. Extreme precipitation is defined as daily precipitation accumulations exceeding the seasonal 95th percentile. In addition to the classical Brier score, we use a binary loss index to assess skill. The binary loss index is tailored to assess the skill of rare events. We analyze daily events that are locally and spatially aggregated, as well as 7 d extreme-event counts. Results consistently show a higher skill in winter compared to summer. The regions showing the highest skill are Norway, Portugal and the south of the Alps. Skill increases when aggregating the extremes spatially or temporally. The verification methodology can be adapted and applied to other variables, e.g., temperature extremes or river discharge.</p

Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps – a matter of model limitations or unpredictable nature?

A rain-on-snow flood occurred in the Bernese Alps, Switzerland, on 10 October 2011, and caused significant damage. As the flood peak was unpredicted by the flood forecast system, questions were raised concerning the causes and the predictability of the event. Here, we aimed to reconstruct the anatomy of this rain-on-snow flood in the Lötschen Valley (160 km²) by analyzing meteorological data from the synoptic to the local scale and by reproducing the flood peak with the hydrological model WaSiM-ETH (Water Flow and Balance Simulation Model). This in order to gain process understanding and to evaluate the predictability. <br><br> The atmospheric drivers of this rain-on-snow flood were (i) sustained snowfall followed by (ii) the passage of an atmospheric river bringing warm and moist air towards the Alps. As a result, intensive rainfall (average of 100 mm day^-1) was accompanied by a temperature increase that shifted the 0° line from 1500 to 3200 m a.s.l. (meters above sea level) in 24 h with a maximum increase of 9 K in 9 h. The south-facing slope of the valley received significantly more precipitation than the north-facing slope, leading to flooding only in tributaries along the south-facing slope. We hypothesized that the reason for this very local rainfall distribution was a cavity circulation combined with a seeder-feeder-cloud system enhancing local rainfall and snowmelt along the south-facing slope. <br><br> By applying and considerably recalibrating the standard hydrological model setup, we proved that both latent and sensible heat fluxes were needed to reconstruct the snow cover dynamic, and that locally high-precipitation sums (160 mm in 12 h) were required to produce the estimated flood peak. However, to reproduce the rapid runoff responses during the event, we conceptually represent likely lateral flow dynamics within the snow cover causing the model to react "oversensitively" to meltwater. <br><br> Driving the optimized model with COSMO (Consortium for Small-scale Modeling)-2 forecast data, we still failed to simulate the flood because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus we conclude that this rain-on-snow flood was, in general, predictable, but requires a special hydrological model setup and extensive and locally precise meteorological input data. Although, this data quality may not be achieved with forecast data, an additional model with a specific rain-on-snow configuration can provide useful information when rain-on-snow events are likely to occur

Magnetodielectric detection of magnetic quadrupole order in Ba(TiO)Cu4_4(PO4_4)4_4 with Cu4_4O12_{12} square cupolas

In vortex-like spin arrangements, multiple spins can combine into emergent multipole moments. Such multipole moments have broken space-inversion and time-reversal symmetries, and can therefore exhibit linear magnetoelectric (ME) activity. Three types of such multipole moments are known: toroidal, monopole, and quadrupole moments. So far, however, the ME-activity of these multipole moments has only been established experimentally for the toroidal moment. Here, we propose a magnetic square cupola cluster, in which four corner-sharing square-coordinated metal-ligand fragments form a noncoplanar buckled structure, as a promising structural unit that carries an ME-active multipole moment. We substantiate this idea by observing clear magnetodielectric signals associated with an antiferroic ME-active magnetic quadrupole order in the real material Ba(TiO)Cu$_4$(PO$_4$)$_4$. The present result serves as a useful guide for exploring and designing new ME-active materials based on vortex-like spin arrangements.Comment: 4 figure

Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events

This study presents a new dynamical downscaling strategy for extreme events. It is based on a combination of statistical downscaling of coarsely resolved global model simulations and dynamical downscaling of specific extreme events constrained by the statistical downscaling part. The method is applied to precipitation extremes over the upper Aare catchment, an area in Switzerland which is characterized by complex terrain. The statistical downscaling part consists of an Artificial Neural Network (ANN) framework trained in a reference period. Thereby, dynamically downscaled precipitation over the target area serve as predictands and large-scale variables, received from the global model simulation, as predictors. Applying the ANN to long term global simulations produces a precipitation series that acts as a surrogate of the dynamically downscaled precipitation for a longer climate period, and therefore are used in the selection of events. These events are then dynamically downscaled with a regional climate model to 2 km. The results show that this strategy is suitable to constraint extreme precipitation events, although some limitations remain, e.g., the method has lower efficiency in identifying extreme events in summer and the sensitivity of extreme events to climate change is underestimated

Tracing troposphere-to-stratosphere transport above a mid-latitude deep convective system

Within the project SPURT (trace gas measurements in the tropopause region) a variety of trace gases have been measured in situ in order to investigate the role of dynamical and chemical processes in the extra-tropical tropopause region. In this paper we report on a flight on 10 November 2001 leading from Hohn, Germany (52�N) to Faro, Portugal (37�N) through a strongly developed deep stratospheric intrusion. This streamer was associated with a large convective system over the western Mediterranean with potentially significant troposphere-to-stratosphere transport. Along major parts of the flight we measured unexpectedly high NOy mixing ratios. Also H2O mixing ratios were significantly higher than stratospheric background levels confirming the extraordinary chemical signature of the probed air masses in the interior of the streamer. Backward trajectories encompassing the streamer enable to analyze the origin and physical characteristics of the air masses and to trace troposphere-to-stratosphere transport. Near the western flank of the streamer features caused by long range transport, such as tropospheric filaments characterized by sudden drops in the O3 and NOy mixing ratios and enhanced CO and H2O can be reconstructed in great detail using the reverse domain filling technique. These filaments indicate a high potential for subsequent mixing with the stratospheric air. At the south-western edge of the streamer a strong gradient in the NOy and the O3 mixing ratios coincides very well with a sharp gradient in potential vorticity in the ECMWF fields. In contrast, in the interior of the streamer the observed highly elevated NOy and H2O mixing ratios up to a potential temperature level of 365K and potential vorticity values of maximum 10 PVU cannot be explained in terms of resolved troposphere-to-stratosphere transport along the backward trajectories. Also mesoscale simulations with a High Resolution Model reveal no direct evidence for convective H2O injection up to this level. Elevated H2O mixing ratios in the ECMWF and HRM are seen only up to about tropopause height at 340 hPa and 270 hPa, respectively, well below flight altitude of about 200 hPa. However, forward tracing of the convective influence as identified by satellite brightness temperature measurements and counts of lightning strokes shows that during this part of the flight the aircraft was closely following the border of an air mass which was heavily impacted by convective activity over Spain and Algeria. This is evidence that deep convection at mid-latitudes may have a large impact on the tracer distribution of the lowermost stratosphere reaching well above the thunderstorms anvils as claimed by recent studies using cloud-resolving models

Machine learning time-local generators of open quantum dynamics

In the study of closed many-body quantum systems one is often interested in the evolution of a subset of degrees of freedom. On many occasions it is possible to approach the problem by performing an appropriate decomposition into a bath and a system. In the simplest case the evolution of the reduced state of the system is governed by a quantum master equation with a time-independent, i.e. Markovian, generator. Such evolution is typically emerging under the assumption of a weak coupling between the system and an infinitely large bath. Here, we are interested in understanding to which extent a neural network function approximator can predict open quantum dynamics-described by time-local generators-from an underlying unitary dynamics. We investigate this question using a class of spin models, which is inspired by recent experimental setups. We find that indeed time-local generators can be learned. In certain situations they are even time-independent and allow to extrapolate the dynamics to unseen times. This might be useful for situations in which experiments or numerical simulations do not allow to capture long-time dynamics and for exploring thermalization occurring in closed quantum systems

Effect of Zai Soil and Water Conservation Technique on Water Balance and the Fate of Nitrate from Organic Amendments Applied: A Case of Degraded Crusted Soils in Niger

Experiments were conducted on degraded crusted soils to study water status and nitrogen release in the soil during the dry seasons of 1999 at ICRISAT research station and on-farm during the rainy seasons of 1999 and 2000 in Niger. Zai is a technology applied on degraded crusted soil, which creates conditions for runoff water harvesting in small pits. The harvested water accumulates in the soil and constitutes a reservoir for plants. The organic amendment applied in the Zai pits releases nutrients for the plants. Soil water status was monitored through weekly measurement with neutron probe; access tubes were installed for the purpose. Nutrient leaching was measured as soil samples were collected three times throughout the cropping season. A rapid progress of the wetting front during the cropping period was observed. It was below 125 cm in the Zai-treated plots 26 days after the rain started versus 60 cm in the non-treated plots. Applying cattle manure leads to shallower water profile due to increased biomass production. Total nitrate content increased throughout the profile compared to the initial status, suggesting possible loss below the plant rooting system due to drainage, which was less pronounced when cattle manure was applied. This study shows that the system improves soil water status allowing plants to escape from dry spells. However, at the same time it can lead to loss of nutrients, particularly nitrogen

Effect of planting technique and amendment type on pearl millet yield, nutrient uptake, and water use on degraded land in Niger

Due to increased population pressure and limited availability of fertile land, farmers on desert fringes increasingly rely on marginal land for agricultural production, which they have learned to rehabilitate with different technologies for soils and water conservation. One such method is the indigenous zai technique used in the Sahel. It combines water harvesting and targeted application of organic amendments by the use of small pits dug into the hardened soil. To study the resource use efficiency of this technique, experiments were conducted 1999–2000, on-station at ICRISAT in Niger, and on-farm at two locations on degraded lands. On-station, the effect of application rate of millet straw and cattle manure on millet dry matter production was studied. On-farm, the effects of organic amendment type (millet straw and cattle manure, at the rate of 300 g per plant) and water harvesting (with and without water harvesting) on millet grain yield, dry matter production, and water use were studied. First, the comparison of zai vs. flat planting, both unamended, resulted in a 3- to 4-fold (in one case, even 19- fold) increase in grain yield on-farm in both years, which points to the yield effects of improved water harvesting in the zai alone. Zai improved the water use efficiency by a factor of about 2. The yields increased further with the application of organic amendments. Manure resulted in 2–68 times better grain yields than no amendment and 2–7 times better grain yields than millet straw (higher on the more degraded soils). Millet dry matter produced per unit of manure N or K was higher than that of millet straw, a tendency that was similar for all rates of application. Zai improved nutrient uptake in the range of 43–64% for N, 50–87% for P and 58–66% for K. Zai increased grain yield produced per unit N (8 vs. 5 kg kg-1) and K (10 vs. 6 kg kg-1) compared to flat; so is the effect of cattle manure compared to millet straw (9 vs. 4 kg kg-1, and 14 vs. 3 kg kg-1), respectively, Therefore zai shows a good potential for increasing agronomic efficiency and nutrient use efficiency. Increasing the rate of cattle manure application from 1 to 3 t ha-1 increased the yield by 115% TDM, but increasing the manure application rate further from 3 to 5 t ha-1 only gave an additional 12% yield increase, which shows that optimum application rates are around 3t ha-

Effect of planting technique and amendment type on pearl millet yield, nutrient uptake, and water use on degraded land in Niger

Due to increased population pressure and limited availability of fertile land, farmers on desert fringes increasingly rely on marginal land for agricultural production, which they have learned to rehabilitate with different technologies for soils and water conservation. One such method is the indigenous zai technique used in the Sahel. It combines water harvesting and targeted application of organic amendments by the use of small pits dug into the hardened soil. To study the resource use efficiency of this technique, experiments were conducted 1999–2000, on-station at ICRISAT in Niger, and on-farm at two locations on degraded lands. On-station, the effect of application rate of millet straw and cattle manure on millet dry matter production was studied. On-farm, the effects of organic amendment type (millet straw and cattle manure, at the rate of 300 g per plant) and water harvesting (with and without water harvesting) on millet grain yield, dry matter production, and water use were studied. First, the comparison of zai vs. flat planting, both unamended, resulted in a 3- to 4-fold (in one case, even 19- fold) increase in grain yield on-farm in both years, which points to the yield effects of improved water harvesting in the zai alone. Zai improved the water use efficiency by a factor of about 2. The yields increased further with the application of organic amendments. Manure resulted in 2–68 times better grain yields than no amendment and 2–7 times better grain yields than millet straw (higher on the more degraded soils). Millet dry matter produced per unit of manure N or K was higher than that of millet straw, a tendency that was similar for all rates of application. Zai improved nutrient uptake in the range of 43–64% for N, 50–87% for P and 58–66% for K. Zai increased grain yield produced per unit N (8 vs. 5 kg kg-1) and K (10 vs. 6 kg kg-1) compared to flat; so is the effect of cattle manure compared to millet straw (9 vs. 4 kg kg-1, and 14 vs. 3 kg kg-1), respectively, Therefore zai shows a good potential for increasing agronomic efficiency and nutrient use efficiency. Increasing the rate of cattle manure application from 1 to 3 t ha-1 increased the yield by 115% TDM, but increasing the manure application rate further from 3 to 5 t ha-1 only gave an additional 12% yield increase, which shows that optimum application rates are around 3t ha-