Precipitation and temperature ensemble forecasts from single-value forecasts

International audienceA procedure is presented to construct ensemble forecasts from single-value forecasts of precipitation and temperature. This involves dividing the spatial forecast domain and total forecast period into a number of parts that are treated as separate forecast events. The spatial domain is divided into hydrologic sub-basins. The total forecast period is divided into time periods, one for each model time step. For each event archived values of forecasts and corresponding observations are used to model the joint distribution of forecasts and observations. The conditional distribution of observations for a given single-value forecast is used to represent the corresponding probability distribution of events that may occur for that forecast. This conditional forecast distribution subsequently is used to create ensemble members that vary in space and time using the "Schaake Shuffle" (Clark et al, 2004). The resulting ensemble members have the same space-time patterns as historical observations so that space-time joint relationships between events that have a significant effect on hydrological response tend to be preserved. Forecast uncertainty is space and time-scale dependent. For a given lead time to the beginning of the valid period of an event, forecast uncertainty depends on the length of the forecast valid time period and the spatial area to which the forecast applies. Although the "Schaake Shuffle" procedure, when applied to construct ensemble members from a time-series of single value forecasts, may preserve some of this scale dependency, it may not be sufficient without additional constraint. To account more fully for the time-dependent structure of forecast uncertainty, events for additional "aggregate" forecast periods are defined as accumulations of different "base" forecast periods. The generated ensemble members can be ingested by an Ensemble Streamflow Prediction system to produce ensemble forecasts of streamflow and other hydrological variables that reflect the meteorological uncertainty. The methodology is illustrated by an application to generate temperature and precipitation ensemble forecasts for the American River in California. Parameter estimation and dependent validation results are presented based on operational single-value forecasts archives of short-range River Forecast Center (RFC) forecasts and medium-range ensemble mean forecasts from the National Weather Service (NWS) Global Forecast System (GFS)

How do I know if my forecasts are better? Using benchmarks in Hydrological ensemble prediction

The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up of the European Flood Awareness System (EFAS) to determine those that are ‘toughest to beat’ and so give the most robust discrimination of forecast skill, particularly for the spatial average fields that EFAS relies upon. Evaluating against an observed discharge proxy the benchmark that has most utility for EFAS and avoids the most naïve skill across different hydrological situations is found to be meteorological persistency. This benchmark uses the latest meteorological observations of precipitation and temperature to drive the hydrological model. Hydrological long term average benchmarks, which are currently used in EFAS, are very easily beaten by the forecasting system and the use of these produces much naïve skill. When decomposed into seasons, the advanced meteorological benchmarks, which make use of meteorological observations from the past 20 years at the same calendar date, have the most skill discrimination. They are also good at discriminating skill in low flows and for all catchment sizes. Simpler meteorological benchmarks are particularly useful for high flows. Recommendations for EFAS are to move to routine use of meteorological persistency, an advanced meteorological benchmark and a simple meteorological benchmark in order to provide a robust evaluation of forecast skill. This work provides the first comprehensive evidence on how benchmarks can be used in evaluation of skill in probabilistic hydrological forecasts and which benchmarks are most useful for skill discrimination and avoidance of naïve skill in a large scale HEPS. It is recommended that all HEPS use the evidence and methodology provided here to evaluate which benchmarks to employ; so forecasters can have trust in their skill evaluation and will have confidence that their forecasts are indeed better

An efficient approach for estimating streamflow forecast skill elasticity

Seasonal streamflow prediction skill can derive from catchment initial hydrological conditions (IHCs) and from the future seasonal climate forecasts (SCFs) used to produce the hydrological forecasts. Although much effort has gone into producing state-of-the-art seasonal streamflow forecasts from improving IHCs and SCFs, these developments are expensive and time consuming and the forecasting skill is still limited in most parts of the world. Hence, sensitivity analyses are crucial to funnel the resources into useful modelling and forecasting developments. It is in this context that a sensitivity analysis technique, the variational ensemble streamflow prediction assessment (VESPA) approach, was recently introduced. VESPA can be used to quantify the expected improvements in seasonal streamflow forecast skill as a result of realistic improvements in its predictability sources (i.e., the IHCs and the SCFs) - termed ‘skill elasticity’ - and to indicate where efforts should be targeted. The VESPA approach is however computationally expensive, relying on multiple hindcasts having varying levels of skill in IHCs and SCFs. This paper presents two approximations of the approach that are computationally inexpensive alternatives. These new methods were tested against the original VESPA results using 30 years of ensemble hindcasts for 18 catchments of the contiguous United States. The results suggest that one of the methods, End Point Blending, is an effective alternative for estimating the forecast skill elasticities yielded by the VESPA approach. The results also highlight the importance of the choice of verification score for a goal-oriented sensitivity analysis

Credit Where Credit is Due: Authorship of Open Ocean Data Workshop Report

Schmidt Ocean Institute, in partnership with The Ditchley Foundation, hosted Credit where credit is due: Authorship of open ocean data at Ditchley Park, in Chipping Norton, UK, on October 6-7, 2022, to identify actionable and implementable solutions to recognize and reward the dissemination of acquired data and knowledge. This report outlines the findings from that workshop

Challenges of operational river forecasting

Skillful and timely streamflow forecasts are critically important to water managers and emergency protection services. To provide these forecasts, hydrologists must predict the behavior of complex coupled human–natural systems using incomplete and uncertain information and imperfect models. Moreover, operational predictions often integrate anecdotal information and unmodeled factors. Forecasting agencies face four key challenges: 1) making the most of available data, 2) making accurate predictions using models, 3) turning hydrometeorological forecasts into effective warnings, and 4) administering an operational service. Each challenge presents a variety of research opportunities, including the development of automated quality-control algorithms for the myriad of data used in operational streamflow forecasts, data assimilation, and ensemble forecasting techniques that allow for forecaster input, methods for using human-generated weather forecasts quantitatively, and quantification of human interference in the hydrologic cycle. Furthermore, much can be done to improve the communication of probabilistic forecasts and to design a forecasting paradigm that effectively combines increasingly sophisticated forecasting technology with subjective forecaster expertise. These areas are described in detail to share a real-world perspective and focus for ongoing research endeavors

La couverture du monument des Néréides

Demargne Pierre. La couverture du monument des Néréides. In: Bulletin de la Société Nationale des Antiquaires de France, 1968, 1970. pp. 54-56

Discours du Président, séance publique annuelle

Demargne Pierre. Discours du Président, séance publique annuelle. In: Comptes rendus des séances de l'Académie des Inscriptions et Belles-Lettres, 124ᵉ année, N. 4, 1980. pp. 672-681

Allocution de M. Pierre Demargne, président

Demargne Pierre. Allocution de M. Pierre Demargne, président. In: Revue des Études Grecques, tome 75, fascicule 356-358, Juillet-décembre 1962. pp. 29-37

l. Nilsson (Martin P.). The Minoan-Mycenaean religion and its survival in Greek religion. Second, revised edition (Acta reg. societatis humaniorum litterarum Lundensis, IX). Lund., C. K. W. Gleerup, 1950

Demargne Pierre. l. Nilsson (Martin P.). The Minoan-Mycenaean religion and its survival in Greek religion. Second, revised edition (Acta reg. societatis humaniorum litterarum Lundensis, IX). Lund., C. K. W. Gleerup, 1950. In: Revue des Études Grecques, tome 67, fascicule 314-315, Janvier-juin 1954. pp. 263-265

Palmarès de l'année 1981

Demargne Pierre. Palmarès de l'année 1981. In: Comptes rendus des séances de l'Académie des Inscriptions et Belles-Lettres, 125ᵉ année, N. 4, 1981. pp. 602-605