scholarly journals The Analogue Method for Precipitation Forecasting: Finding Better Analogue Situations at a Sub-Daily Time Step

2016 ◽  
Author(s):  
Pascal Horton ◽  
Charles Obled ◽  
Michel Jaboyedoff
Keyword(s):  
Time Series ◽  
Atmospheric Circulation ◽  
Time Window ◽  
Heavy Precipitation ◽  
Seasonal Effect ◽  
Precipitation Series ◽  
Time Step ◽  
Analogue Method ◽  
The Impact ◽  
Daily Time

Abstract. The Analogue Method (AM) aims at forecasting local weather variables (predictands), such as precipitations, by means of a statistical relationship with predictors at a synoptic scale. The analogy is generally assessed in the first place on the geopotential field by mean of a comparison of the gradients, in order to sample the days with a similar atmospheric circulation. The search for candidate situations, for a given target day, is usually undertaken by comparing the state of the atmosphere at fixed hours of the day, for both the target day and the candidate analogues. The constraint being the use of daily time series, due to the length of available archives they provide, and the unavailability of equivalent archives at a finer time step. However, it is unlikely that the best analogy happens at the very same hour, but it may occur at a different time of the day. In order to assess the potential of finding better analogues at a different hour, a moving time window (MTW) has been introduced on a reduced archive of hourly precipitation totals. The MTW resulted in a better analogy in terms of the atmospheric circulation, with improved values of the analogy criteria on the whole distribution of analogue dates. The improvement was found to grow with the analogue ranks due to an accumulation of more similar situations in the selection. Moreover, the improvement is even more important for days with heavy precipitation events, which are generally related to more dynamic atmospheric situations, where timing is more specific. A seasonal effect has also been identified, with larger improvements in winter than in summer, supposedly due to the stronger effect of the diurnal cycle in summer, which favors predictors at the same hour for target and analogues. The impact of the MTW on the prediction performance has been assessed by means of a sub-daily precipitation series transformed into moving 24 h-totals at a 6-hourly time step. This resulted in an improvement of the prediction skills, which were even larger after recalibrating the AM parameters. However, attempts to reconstruct longer precipitation series of running 24 h-totals by means of simple methods failed. It emphasized the need to use time series with an appropriate chronology. These should be available in a near future, either by means of growing observed archives, or by the establishment of precipitation reanalyses through regional modeling. Then, the use of a MTW in the AM should be considered for any application, especially when the prediction quality of extreme events is important.

scholarly journals The analogue method for precipitation prediction: finding better analogue situations at a sub-daily time step

2017 ◽  
Vol 21 (7) ◽  
pp. 3307-3323 ◽  
Author(s):  
Pascal Horton ◽  
Charles Obled ◽  
Michel Jaboyedoff
Keyword(s):  
Atmospheric Circulation ◽  
Daily Precipitation ◽  
Time Window ◽  
Heavy Precipitation ◽  
Prediction Skill ◽  
Time Shift ◽  
Seasonal Effect ◽  
Time Step ◽  
Precipitation Prediction ◽  
The Impact

Abstract. Analogue methods (AMs) predict local weather variables (predictands) such as precipitation by means of a statistical relationship with predictors at a synoptic scale. The analogy is generally assessed on gradients of geopotential heights first to sample days with a similar atmospheric circulation. Other predictors such as moisture variables can also be added in a successive level of analogy. The search for candidate situations similar to a given target day is usually undertaken by comparing the state of the atmosphere at fixed hours of the day for both the target day and the candidate analogues. This is a consequence of using standard daily precipitation time series, which are available over longer periods than sub-daily data. However, it is unlikely for the best analogy to occur at the exact same hour for the target and candidate situations. A better analogue situation may be found with a time shift of several hours since a better fit can occur at different times of the day. In order to assess the potential for finding better analogues at a different hour, a moving time window (MTW) has been introduced. The MTW resulted in a better analogy in terms of the atmospheric circulation and showed improved values of the analogy criterion on the entire distribution of the extracted analogue dates. The improvement was found to increase with the analogue rank due to an accumulation of better analogues in the selection. A seasonal effect has also been identified, with larger improvements shown in winter than in summer. This may be attributed to stronger diurnal cycles in summer that favour predictors taken at the same hour for the target and analogue days. The impact of the MTW on the precipitation prediction skill has been assessed by means of a sub-daily precipitation series transformed into moving 24 h totals at 12, 6, and 3 h time steps. The prediction skill was improved by the MTW, as was the reliability of the prediction. Moreover, the improvements were greater for days with heavy precipitation, which are generally related to more dynamic atmospheric situations in which the timing is more specific and for which fewer records are available in the meteorological archive. The improvements of the analogy criterion and the performance scores on precipitation were both found to be higher for MTWs with a smaller time step of 3 h. A 3 h MTW provides 8 times more candidate situations even though they are not fully independent. Since the MTW provides additional situations to the pool of possible analogues, it can be considered as an inflation of the meteorological archive. Because this technique is simple and easily applicable, it should be considered for several applications in different contexts, such as operational forecasting or climate-related studies.

scholarly journals Assessing dry weather flow contribution in TSS and COD storm events loads in combined sewer systems

2011 ◽  
Vol 63 (12) ◽  
pp. 2983-2991 ◽  
Author(s):  
M. Métadier ◽  
J. L. Bertrand-Krajewski
Keyword(s):  
Time Series ◽  
Oxygen Demand ◽  
Seasonal Effect ◽  
Storm Events ◽  
Combined System ◽  
Time Step ◽  
Urban Catchment ◽  
Sewer Systems ◽  
Continuous Discharge

Continuous high resolution long term turbidity measurements along with continuous discharge measurements are now recognised as an appropriate technique for the estimation of in sewer total suspended solids (TSS) and Chemical Oxygen Demand (COD) loads during storm events. In the combined system of the Ecully urban catchment (Lyon, France), this technique is implemented since 2003, with more than 200 storm events monitored. This paper presents a method for the estimation of the dry weather (DW) contribution to measured total TSS and COD event loads with special attention devoted to uncertainties assessment. The method accounts for the dynamics of both discharge and turbidity time series at two minutes time step. The study is based on 180 DW days monitored in 2007–2008. Three distinct classes of DW days were evidenced. Variability analysis and quantification showed that no seasonal effect and no trend over the year were detectable. The law of propagation of uncertainties is applicable for uncertainties estimation. The method has then been applied to all measured storm events. This study confirms the interest of long term continuous discharge and turbidity time series in sewer systems, especially in the perspective of wet weather quality modelling.

scholarly journals Spatial relationship between the atmospheric circulation and the precipitation measured in the western Swiss Alps by means of the analogue method

2012 ◽  
Vol 12 (3) ◽  
pp. 777-784 ◽  
Author(s):  
P. Horton ◽  
M. Jaboyedoff ◽  
R. Metzger ◽  
C. Obled ◽  
R. Marty
Keyword(s):  
Atmospheric Circulation ◽  
Precipitation Amount ◽  
Heavy Precipitation ◽  
Swiss Alps ◽  
Precipitation Event ◽  
Circulation Patterns ◽  
Analogue Method ◽  
Western Swiss Alps ◽  
Time Extrapolation ◽  
Precipitation Events

Abstract. An adaptation technique based on the synoptic atmospheric circulation to forecast local precipitation, namely the analogue method, has been implemented for the western Swiss Alps. During the calibration procedure, relevance maps were established for the geopotential height data. These maps highlight the locations were the synoptic circulation was found of interest for the precipitation forecasting at two rain gauge stations (Binn and Les Marécottes) that are located both in the alpine Rhône catchment, at a distance of about 100 km from each other. These two stations are sensitive to different atmospheric circulations. We have observed that the most relevant data for the analogue method can be found where specific atmospheric circulation patterns appear concomitantly with heavy precipitation events. Those skilled regions are coherent with the atmospheric flows illustrated, for example, by means of the back trajectories of air masses. Indeed, the circulation recurrently diverges from the climatology during days with strong precipitation on the southern part of the alpine Rhône catchment. We have found that for over 152 days with precipitation amount above 50 mm at the Binn station, only 3 did not show a trajectory of a southerly flow, meaning that such a circulation was present for 98% of the events. Time evolution of the relevance maps confirms that the atmospheric circulation variables have significantly better forecasting skills close to the precipitation period, and that it seems pointless for the analogue method to consider circulation information days before a precipitation event as a primary predictor. Even though the occurrence of some critical circulation patterns leading to heavy precipitation events can be detected by precursors at remote locations and 1 week ahead (Grazzini, 2007; Martius et al., 2008), time extrapolation by the analogue method seems to be rather poor. This would suggest, in accordance with previous studies (Obled et al., 2002; Bontron and Obled, 2005), that time extrapolation should be done by the Global Circulation Model, which can process atmospheric variables that can be used by the adaptation method.

scholarly journals Atmospheric circulation patterns associated with the variability of River Ammer floods: evidence from observed and proxy data

2016 ◽  
Vol 12 (2) ◽  
pp. 377-385 ◽  
Author(s):  
Norel Rimbu ◽  
Markus Czymzik ◽  
Monica Ionita ◽  
Gerrit Lohmann ◽  
Achim Brauer
Keyword(s):  
Time Series ◽  
Atmospheric Circulation ◽  
Western Europe ◽  
Wave Train ◽  
Heavy Precipitation ◽  
Circulation Pattern ◽  
Flood Frequency ◽  
Discharge Data ◽  
Western Asia ◽  
Instrumental Period

Abstract. The relationship between the frequency of River Ammer floods (southern Germany) and atmospheric circulation variability is investigated based on observational Ammer River discharge data back to 1926 and a flood layer time series from varved sediments of the downstream Lake Ammer for the pre-instrumental period back to 1766. A composite analysis reveals that, at synoptic timescales, observed River Ammer floods are associated with enhanced moisture transport from the Atlantic Ocean and the Mediterranean towards the Ammer region, a pronounced trough over western Europe as well as enhanced potential vorticity at upper levels. We argue that this synoptic-scale configuration can trigger heavy precipitation and floods in the Ammer region. Interannual to multidecadal increases in flood frequency, as detected in the instrumental discharge record, are associated with a wave train pattern extending from the North Atlantic to western Asia, with a prominent negative center over western Europe. A similar atmospheric circulation pattern is associated with increases in flood layer frequency in the Lake Ammer sediment record during the pre-instrumental period. We argue that the complete flood layer time series from Lake Ammer sediments covering the last 5500 years contains information about atmospheric circulation variability on interannual to millennial timescales.

Using a high-resolution regional climate model large ensemble to simulate the impact of extreme precipitation on flooding over small to medium-size catchments

2021 ◽  
Author(s):  
Mina Faghih ◽  
François Brissette ◽  
Parham Sabeti ◽  
Mostafa Tarek
Keyword(s):  
Return Period ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Large Ensemble ◽  
Catchment Scale ◽  
Time Step ◽  
Daily Time Step ◽  
The Impact ◽  
Small Catchments ◽  
Daily Time

<p>Recent studies show that the frequency and intensity of extreme precipitation will increase under a warmer climate. It is expected that extreme convective precipitation will scale at a larger than Clausius–Clapeyron rate and especially so for short-duration rainfall. This has implication on flooding risk, and especially so on small catchments (<500 km<sup>2</sup>) which have a quick response time and are therefore particularly vulnerable to short duration rainfall. The impact of the amplification of extreme precipitation as a function of catchment scale has not been widely studied because most of the climate change impact studies have been conducted at the daily time step or higher. This is because until recently the vast majority of climate model outputs have only been available at the daily time step.</p><p>This study has looked at the amplification of sub-daily, daily, and multiday extreme precipitation and flooding and its dependency on catchment scale. This work uses outputs from the Climex large-ensemble to study the amplification of extreme streamflow with return period from 2 to 300 years and durations from 1 to 24 hours over 133 North-American catchments. Using a large ensemble allows for the accurate empirical computation of extreme events with very large return periods.  Results indicate that future extreme streamflow relative increases are largest for smaller catchments, longer return period, and shorter rainfall durations. Small catchments are therefore more vulnerable to future extreme rainfall than their larger counterparts.</p>

scholarly journals The Impact of Gridded Weather Database on Soil Water Availability in Rice Crop Modeling

2021 ◽  
Author(s):  
Caio Teodoro Menezes ◽  
Derblai Casaroli ◽  
Alexandre Bryan Heinemann ◽  
Vinicius Cintra Moschetti ◽  
Rafael Battisti
Keyword(s):  
Sandy Soil ◽  
Upland Rice ◽  
Crop Modeling ◽  
Time Step ◽  
R And D ◽  
Daily Time Step ◽  
D Values ◽  
Attainable Yield ◽  
The Impact ◽  
Daily Time

Abstract In recent years, there has been an increase in studies suggesting that gridded weather database (GWD) is a suitable source for simulating crop yield. Brazil has low geospatial coverage by measured weather database (MWD). Based on that, this study aimed to compare two different GWD sources, Daily Gridded (DG) and NASA/POWER (NP), on the simulated yield of upland rice (UR) against the MWD input. The GWD and MWD were obtained for seven locations across UR Brazilian region, considering a period ranging from 1984 to 2016. GWD and MWD were used to estimate rice potential (Yp) and attainable yield (Ya), in clay soil and sandy soil, using ORYZA (v3) model. DG had the best performance for all variables. GWD-based yields had a reasonable performance. However, DG had a slightly better performance than NP in all conditions, DG-based yields showed RMSE values of 0.57, 0.71 and 0.52 for Yp and Ya in clay and sandy soil, whereas NP showed RMSE values of 0.86, 0.91 and 0.64. DG also showed higher R² and d values for yields assessed. Both GWD overestimated Ya, these overestimations in DG-based yield were 3.54, 9.61, and 21.35% for Yp and Ya in clay and sandy soil respectively, in NP-based yield were 13.67, 18.45, 29.11%, showing that for both GWD-based yield increased as the soil type texture as well as water storage decreased. As a consequence, we do not recommend the use of precipitation data in daily time-step crop modeling.

scholarly journals Sensitivity of ensemble Lagrangian reconstructions to assimilated wind time step resolution

2010 ◽  
Vol 10 (7) ◽  
pp. 3155-3162 ◽  
Author(s):  
I. Pisso ◽  
V. Marécal ◽  
B. Legras ◽  
G. Berthet
Keyword(s):  
Time Series ◽  
Transport Model ◽  
Positive Impact ◽  
Wind Fields ◽  
Time Step ◽  
Chemistry Transport Model ◽  
Temporal And Spatial ◽  
The Impact ◽  
Optimal Space

Abstract. We study the impact of temporal and spatial resolution and changes in modelled meteorological winds in the context of diffusive ensemble Lagrangian reconstructions. In situ tracer measurements are modelled based on coarse resolution global 3-D tracer distributions from a chemistry-transport model and on different time series of meteorological wind fields including a special set of 1-hourly analysed winds which is compared with 3 and 6-hourly operational analysed winds and with 3-hourly ERA-interim reanalysis. Increasing the time resolution of the advecting winds from three to one hour using the operational winds provides an improvement on diffusive reconstructions in the period studied but smaller than that obtained from six to three hours. The positive impact of using 1-hourly winds is similar to that obtained using ERA-Interim 3-hourly winds instead of the 3-hourly ECMWF operational analysis for the same period. This study sets out a technique to quantify differences in time series of meteorological wind fields here applied to assess the optimal space and time resolutions for ensemble Lagrangian reconstructions in the lower stratosphere.

scholarly journals Data assimilation experiments using diffusive back-and-forth nudging for the NEMO ocean model

2015 ◽  
Vol 22 (2) ◽  
pp. 233-248 ◽  
Author(s):  
G. A. Ruggiero ◽  
Y. Ourmières ◽  
E. Cosme ◽  
J. Blum ◽  
D. Auroux ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Time Window ◽  
Ocean Model ◽  
Time Step ◽  
Sensitivity Tests ◽  
Set Up ◽  
The Impact ◽  
Backward Integration ◽  
Reversed Time ◽  
Data Assimilation System

Abstract. The diffusive back-and-forth nudging (DBFN) is an easy-to-implement iterative data assimilation method based on the well-known nudging method. It consists of a sequence of forward and backward model integrations, within a given time window, both of them using a feedback term to the observations. Therefore, in the DBFN, the nudging asymptotic behaviour is translated into an infinite number of iterations within a bounded time domain. In this method, the backward integration is carried out thanks to what is called backward model, which is basically the forward model with reversed time step sign. To maintain numeral stability, the diffusion terms also have their sign reversed, giving a diffusive character to the algorithm. In this article the DBFN performance to control a primitive equation ocean model is investigated. In this kind of model non-resolved scales are modelled by diffusion operators which dissipate energy that cascade from large to small scales. Thus, in this article, the DBFN approximations and their consequences for the data assimilation system set-up are analysed. Our main result is that the DBFN may provide results which are comparable to those produced by a 4Dvar implementation with a much simpler implementation and a shorter CPU time for convergence. The conducted sensitivity tests show that the 4Dvar profits of long assimilation windows to propagate surface information downwards, and that for the DBFN, it is worth using short assimilation windows to reduce the impact of diffusion-induced errors. Moreover, the DBFN is less sensitive to the first guess than the 4Dvar.

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