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1.
Patricia de Rosnay Gianpaolo Balsamo Clément Albergel Joaquín Muñoz-Sabater Lars Isaksen 《Surveys in Geophysics》2014,35(3):607-621
Land surface processes and their initialisation are of crucial importance for Numerical Weather Prediction (NWP). Current land data assimilation systems used to initialise NWP models include snow depth analysis, soil moisture analysis, soil temperature and snow temperature analysis. This paper gives a review of different approaches used in NWP to initialise land surface variables. It discusses the observation availability and quality, and it addresses the combined use of conventional observations and satellite data. Based on results from the European Centre for Medium-Range Weather Forecasts (ECMWF), results from different soil moisture and snow depth data assimilation schemes are shown. Both surface fields and low-level atmospheric variables are highly sensitive to the soil moisture and snow initialisation methods. Recent developments of ECMWF in soil moisture and snow data assimilation improved surface and atmospheric forecast performance. 相似文献
2.
The mesoscale Numerical Weather Prediction (NWP) model is gaining popularity among the hydrometeorological community in providing high‐resolution rainfall forecasts at the catchment scale. Although the performance of the model has been verified in capturing the physical processes of severe storm events, the modelling accuracy is negatively affected by significant errors in the initial conditions used to drive the model. Several meteorological investigations have shown that the assimilation of real‐time observations, especially the radar data can help improve the accuracy of the rainfall predictions given by mesoscale NWP models. The aim of this study is to investigate the effect of data assimilation for hydrological applications at the catchment scale. Radar reflectivity together with surface and upper‐air meteorological observations is assimilated into the Weather Research and Forecasting (WRF) model using the three‐dimensional variational data‐assimilation technique. Improvement of the rainfall accumulation and its temporal variation after data assimilation is examined for four storm events in the Brue catchment (135.2 km2) located in southwest England. The storm events are selected with different rainfall distributions in space and time. It is found that the rainfall improvement is most obvious for the events with one‐dimensional evenness in either space or time. The effect of data assimilation is even more significant in the innermost domain which has the finest spatial resolution. However, for the events with two‐dimensional unevenness of rainfall, i.e. the rainfall is concentrated in a small area and in a short time period, the effect of data assimilation is not ideal. WRF fails in capturing the whole process of the highly convective storm with densely concentrated rainfall in a small area and a short time period. A shortened assimilation time interval together with more efficient utilisation of the weather radar data might help improve the effectiveness of data assimilation in such cases. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
3.
This paper presents a comparison of two reduced-order, sequential, and variational data assimilation methods: the singular
evolutive extended Kalman filter (SEEK) and the reduced 4D-Var (R-4D-Var). A hybridization of the two, combining the variational
framework and the sequential evolution of covariance matrices, is also preliminarily investigated and assessed in the same
experimental conditions. The comparison is performed using the twin-experiment approach on a model of the tropical Pacific
domain. The assimilated data are simulated temperature profiles at the locations of the TAO/TRITON array moorings. It is shown
that, in a quasilinear regime, both methods produce similarly good results. However, the hybrid approach provides slightly
better results and thus appears as potentially fruitful. In a more nonlinear regime, when tropical instability waves develop,
the global nature of the variational approach helps control model dynamics better than the sequential approach of the SEEK
filter. This aspect is probably enhanced by the context of the experiments in that there is a limited amount of assimilated
data and no model error. 相似文献
4.
In this paper, a feasibility of anelastic approach for numerical weather prediction (NWP) is examined. The study concerns
the anelastic nonhydrostatic model EULAG as a prospective candidate for the new dynamical core of a high-resolution NWP model.
Such an application requires a series of benchmark tests to be performed. The study presents the results of dry idealized
two-dimensional linear and non-linear tests. They include evolution of cold and warm density currents in neutrally stratified
atmosphere, inertia-gravity waves in short and long channels, as well as mountain gravity waves for a set of different flow
regimes. Detailed comparison of the results with the reference solutions, based mainly on the results of compressible models,
indicates a high level of conformity for all of the experiments. It verifies the anelastic approach as strongly consistent
with the compressible one for a broad class of atmospheric problems. It also corroborates the robustness of EULAG numerics,
an essential requirement of dynamical core of NWP model. 相似文献
5.
S. Abhilash A. K. Sahai K. Mohankumar John P. George Someshwar Das 《Pure and Applied Geophysics》2012,169(11):2047-2070
In this paper the impact of Doppler weather radar (DWR) reflectivity and radial velocity observations for the short range forecasting of a tropical storm and associated rainfall event have been examined. Doppler radar observations of a tropical storm case that occurred during 29–30 October 2006 from SHARDWR (13.6° N, 80.2° E) are assimilated in the WRF 3DVAR system. The observation operator for radar reflectivity and radial velocity is included within latest version of WRF 3DVAR system. Keeping all model physics the same, three experiments were conducted at a horizontal resolution of 30?km. In the control experiment (CTRL), NCEP Final Analysis (FNL) interpolated to the model grid was used as the initial condition for 48-h free forecast. In the second experiment (NODWR), 6-h assimilation cycles have been carried out using all conventional (radiosonde and surface data) and non-conventional (satellite) observations from the Global Telecommunication System (GTS). The third experiment (DWR) is the same as the second, except Doppler radar radial velocity and reflectivity observations are also used in the assimilation cycle. Continuous 6-h assimilation cycle employed in the WRF-3DVAR system shows positive impact on the rainfall forecast. Assimilation of DWR data creates several small scale features near the storm centre. Additional sensitivity experiments were conducted to study the individual impact of reflectivity and radial velocity in the assimilation cycle. Radar data assimilation with reflectivity alone produced large analysis response on both thermodynamical and dynamical fields. However, radial velocity assimilation impacted only on dynamical fields. Analysis increments with radar reflectivity and radial velocity produce adjustments in both dynamical and thermodynamical fields. Verification of QPF skill shows that radar data assimilation has a considerable impact on the short range precipitation forecast. Improvement of the QPF skill with radar data assimilation is more clearly seen in the heavy rainfall (for thresholds >7?mm) event than light rainfall (for thresholds of 1 and 3?mm). The spatial pattern of rainfall is well simulated by the DWR experiment and is comparable to TRMM observations. 相似文献
6.
本文利用美国海军台风警报中心（JTWC）提供的1945～2002年热带风暴路径资料统计分析了西北太平洋（NWP）和中国南海（SCS）风暴生成及登陆中国大陆热带风暴的时空演变特征.季节变化上，NWP风暴登陆主要集中于6～11月，SCS风暴影响主要集中在6～9月，但后者登陆总数比前者少.西北太平洋风暴在东南沿海(27°N，120°E)附近登陆的频次最高，在此以北随纬度急剧下降.年际变化时间尺度上，登陆大陆的风暴年总数与来自南海的年风暴数成正比.登陆我国的热带风暴年频数有明显的区域差异和显著的2～7年振荡.长期趋势上，两个海域的风暴年生成频数和登陆大陆的年风暴频数在58年中总体呈线性增长趋势，其中登陆频数增长趋势相对缓慢，但近几年登陆风暴数与生成风暴数都表现出减少的趋势.生成频数和登陆频数都呈现出年代际变化，其年代转换发生在1960、1970年和1990年前后. 相似文献
7.
This study explores for the first time the impact of assimilating radial velocity (Vr) observations from a single or multiple Taiwan’s coastal radars on tropical cyclone (TC) forecasting after landfall in the Chinese mainland by using a Weather Research and Forecasting model (WRF)-based ensemble Kalman filter (EnKF) data assimilation system. Typhoon Morakot (2009), which caused widespread damage in the southeastern coastal regions of the mainland after devastating Taiwan, was chosen as a case study. The results showed that assimilating Taiwan’s radar Vr data improved environmental field and steering flow and produced a more realistic TC position and structure in the final EnKF cycling analysis. Thus, the subsequent TC track and rainfall forecasts in southeastern China were improved. In addition, better observations of the TC inner core by Taiwan’s radar was a primary factor in improving TC rainfall forecast in the Chinese mainland. 相似文献
8.
To respond to the need for preventing offshore and coastal accidents, damage and flooding, a state-of-the-art coastal wave forecast system for the East Coast of Korea waters is being developed. Given that the quality of the input wind has been identified as the main factor influencing the quality of the wave results, the effectiveness of adjusting the wind fields by means of data assimilation using the ensemble Kalman filter technique has been explored. In this article the model setup, the data assimilation parameters and the validation of the predictions during stormy periods is described. The validation shows that the model is able to provide predictions of coastal waves fulfilling available benchmarks; especially, the data assimilation analysis and forecast predictions are judged to be of high quality. 相似文献
9.
Based on the Kalman filter theory, a new data-assimilation method has been used to improve the 3-D oceanic temperature field
of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled general circulation model. This method is applied to assimilate
surface and subsurface temperature of in situ measurements from the Pilot Research Moored Array in the Tropical Atlantic project
(PIRATA). The assimilation of the PIRATA data produces an improved representation of the thermal state of the ocean and allows
a better estimation of other oceanographic quantities, like meridional heat fluxes and zonal currents. The present paper focuses
on the tropical Atlantic and, in particular, it contains new reconstructed temperature profiles. One-month forecast experiments
during 1999 were performed and the impact of the assimilation is discussed.
Received: 24 April 2001 / Accepted: 8 March 2002 相似文献
10.
The tropical Indian Ocean experiences an interannual mode of climatic variability, known as the Indian Ocean Dipole (IOD). The signature of this variability in ocean salinity is hypothesized based on modeling and assimilation studies, on account of scanty observations. Soil Moisture and Ocean Salinity (SMOS) satellite has been designed to take up the challenge of sea surface salinity remote sensing. We show that SMOS data can be used to infer the pattern of salinity variability linked with the IOD events. The core of maximum variability is located in the central tropical basin, south of the equator. This region is anomalously salty during the 2010 negative IOD event, and anomalously fresh during the 2011 positive IOD event. The peak-to-peak anomaly exceeds one salinity unit, between late 2010 and late 2011. In conjunction with other observational datasets, SMOS data allow us to draw the salt budget of the area. It turns out that the horizontal advection is the main driver of salinity anomalies. This finding is confirmed by the analysis of the outputs of a numerical model. This study shows that the advent of SMOS makes it feasible the quantitative assessment of the mechanisms of ocean surface salinity variability in the tropical basins, at interannual timescales. 相似文献
11.
This paper presents the verification results of nowcasts of four continuous variables generated from an integrated weighted model and underlying Numerical Weather Prediction (NWP) models. Real-time monitoring of fast changing weather conditions and the provision of short term forecasts, or nowcasts, in complex terrain within coastal regions is challenging to do with sufficient accuracy. A recently developed weighting, evaluation, bias correction and integration system was used in the Science of Nowcasting Olympic Weather for Vancouver 2010 project to generate integrated weighted forecasts (INTW) out to 6 h. INTW forecasts were generated with in situ observation data and background gridded forecasting data from Canadian high-resolution deterministic NWP system with three nested grids at 15-, 2.5- and 1-km horizontal grid-spacing configurations. In this paper, the four variables of temperature, relative humidity, wind speed and wind gust are treated as continuous variables for verifying the INTW forecasts. Fifteen sites were selected for the comparison of the model performances. The results of the study show that integrating surface observation data with the NWP forecasts produce better statistical scores than using either the NWP forecasts or an objective analysis of observed data alone. Overall, integrated observation and NWP forecasts improved forecast accuracy for the four continuous variables. The mean absolute errors from the INTW forecasts for the entire test period (12 February to 21 March 2010) are smaller than those from NWP forecasts with three configurations. The INTW is the best and most consistent performer among all models regardless of location and variable analyzed. 相似文献
12.
Mesoscale eddy plays an important role in the ocean circulation. In order to improve the simulation accuracy of the mesoscale eddies, a three-dimensional variation (3DVAR) data assimilation system called Ocean Variational Analysis System (OVALS) is coupled with a POM model to simulate the mesoscale eddies in the Northwest Pacific Ocean. In this system, the sea surface height anomaly (SSHA) data by satellite altimeters are assimilated and translated into pseudo temperature and salinity (T-S) profile data. Then, these profile data are taken as observation data to be assimilated again and produce the three-dimensional analysis T-S field. According to the characteristics of mesoscale eddy, the most appropriate assimilation parameters are set up and testified in this system. A ten years mesoscale eddies simulation and comparison experiment is made, which includes two schemes: assimilation and non-assimilation. The results of comparison between two schemes and the observation show that the simulation accuracy of the assimilation scheme is much better than that of non-assimilation, which verified that the altimetry data assimilation method can improve the simulation accuracy of the mesoscale dramatically and indicates that it is possible to use this system on the forecast of mesoscale eddies in the future. 相似文献
13.
The tropical Indian Ocean experiences an interannual mode of climatic variability, known as the Indian Ocean Dipole (IOD). The signature of this variability in ocean salinity is hypothesized based on modeling and assimilation studies, on account of scanty observations. Soil Moisture and Ocean Salinity (SMOS) satellite has been designed to take up the challenge of sea surface salinity remote sensing. We show that SMOS data can be used to infer the pattern of salinity variability linked with the IOD events. The core of maximum variability is located in the central tropical basin, south of the equator. This region is anomalously salty during the 2010 negative IOD event, and anomalously fresh during the 2011 positive IOD event. The peak-to-peak anomaly exceeds one salinity unit, between late 2010 and late 2011. In conjunction with other observational datasets, SMOS data allow us to draw the salt budget of the area. It turns out that the horizontal advection is the main driver of salinity anomalies. This finding is confirmed by the analysis of the outputs of a numerical model. This study shows that the advent of SMOS makes it feasible the quantitative assessment of the mechanisms of ocean surface salinity variability in the tropical basins, at interannual timescales.
相似文献14.
15.
This paper investigates the effect of adjusting the mean field bias (MFB) in radar-based precipitation data on analysis and prediction of streamflow and soil moisture in assimilating streamflow or streamflow and in situ soil moisture data into distributed hydrologic models. To evaluate the effect of adjusting the MFB under realistic as well as idealized conditions, both real-world and synthetic experiments are carried out for the Eldon Catchment on the border of Oklahoma and Arkansas in the US. In the synthetic experiment, the MFB is modeled as a stationary Markov chain process. The synthetic experiment showed that adjusting the MFB in the assimilation process significantly improves streamflow analysis when the initial conditions are known with reasonable certainty, and that assimilating soil moisture in addition to streamflow improves analysis of streamflow as well as soil moisture if the initial conditions are largely uncertain. Adjusting the MFB during the assimilation process noticeably improved streamflow analysis over ranges of the MFB and random noise in the precipitation data. On the other hand, increasing the MFB and random noise in the precipitation data tended to degrade soil moisture analysis due possibly to over-adjusting soil moisture to mitigate the precipitation error. The real-world experiment with one-year dataset showed that adjusting the MFB during the assimilation process helped capture the peak as well as volume of outlet flow analysis as well as prediction, and that additionally assimilating interior flow observations was necessary to improve analysis and prediction of peak flows at interior locations. 相似文献
16.
Thierry Bergot 《Pure and Applied Geophysics》2007,164(6-7):1265-1282
Short-term forecasting of fog is a difficult issue which can have a large societal impact. Fog appears in the surface boundary
layer and is driven by the interactions between land surface and the lower layers of the atmosphere. These interactions are
still not well parameterized in current operational NWP models, and a new methodology based on local observations, an adaptive
assimilation scheme and a local numerical model is tested. The proposed numerical forecast method of foggy conditions has
been run during three years at Paris-CdG international airport. This test over a long-time period allows an in-depth evaluation
of the forecast quality. This study demonstrates that detailed 1-D models, including detailed physical parameterizations and
high vertical resolution, can reasonably represent the major features of the life cycle of fog (onset, development and dissipation)
up to +6 h. The error on the forecast onset and burn-off time is typically 1 h. The major weakness of the methodology is related
to the evolution of low clouds (stratus lowering). Even if the occurrence of fog is well forecasted, the value of the horizontal
visibility is only crudely forecasted. Improvements in the microphysical parameterization and in the translation algorithm
converting NWP prognostic variables into a corresponding horizontal visibility seems necessary to accurately forecast the
value of the visibility. 相似文献
17.
This paper presents the verification results for nowcasts of seven categorical variables from an integrated weighted model (INTW) and the underlying numerical weather prediction (NWP) models. Nowcasting, or short range forecasting (0–6 h), over complex terrain with sufficient accuracy is highly desirable but a very challenging task. A weighting, evaluation, bias correction and integration system (WEBIS) for generating nowcasts by integrating NWP forecasts and high frequency observations was used during the Vancouver 2010 Olympic and Paralympic Winter Games as part of the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) project. Forecast data from Canadian high-resolution deterministic NWP system with three nested grids (at 15-, 2.5- and 1-km horizontal grid-spacing) were selected as background gridded data for generating the integrated nowcasts. Seven forecast variables of temperature, relative humidity, wind speed, wind gust, visibility, ceiling and precipitation rate are treated as categorical variables for verifying the integrated weighted forecasts. By analyzing the verification of forecasts from INTW and the NWP models among 15 sites, the integrated weighted model was found to produce more accurate forecasts for the 7 selected forecast variables, regardless of location. This is based on the multi-categorical Heidke skill scores for the test period 12 February to 21 March 2010. 相似文献
18.
Recent observations of the tropical and subtropical atmosphere are interpreted in terms of scaling arguments and wave propagation theory advanced byCharney (1963, 1969).Charney’s idealizations describe the tropical atmosphere in terms of large regions of quasi-nondivergent flow containing small subdomains of heavy convection and divergence, and place emphasis upon the quasi-rotational regions. FGGE (First GARP Global Experiment) observations suggest that strongly divergent local tropical circulations are forced by latent heating and produce important direct modifications of the total wind field. We describe the extent to which the resulting field consists of divergent and rotational components in different analyses of the FGGE data, and present independent supporting documentation of the results in terms of heating estimates and rainfall observations. Local tropical heating rates on the order of 10°C/day are apparently due to latent heat release associated with precipitation rates as large as 6 cm/day during extended periods. The large contribution of the divergent wind is generally underestimated in models that do not retain such energetic local forcings, and this deficiency may be related to general underestimation of tropical-extratropical connections of many linear models. Such connections are commonly cited in relation to El Niño events, the Southern Hemisphere stationary-wave pattern, and in FGGE studies, but are not well simulated in most linear theories. It is not yet clear whether this is an inherent limitation of linear models, or whether the linear models have not yet explored all the potentially relevant ambient states. We explore the latter possibility by construction of a basic state that allows reasonable latitudinal evolution of the wave field. This basic state has zero absolute vorticity gradient throughout the tropics, and deviations linearized about this state are dynamically analogous to a “local” Hadley cell. To the extent that it is appropriate to regard the results in terms of wave propagation, our analysis suggests a prominent role for gravity-inertia waves in the tropics and for the extratropical connections. The relevance of gravity modes to observations and the theoretical explanation of the flat vorticity field remain to be established. 相似文献
19.
Matthew K. MacDonald Bruce J. Davison Muluneh A. Mekonnen Alain Pietroniro 《水文科学杂志》2013,58(16):2860-2871
ABSTRACTThe low density of meteorological stations in parts of Canada necessitates using numerical weather prediction (NWP)/assimilation output for hydrological modelling. In this study, comparisons are made of simulated land surface variables when using field observations versus NWP output as forcing for two well-instrumented sites: the mountainous and forested Marmot Creek Basin (MCRB) in the Canadian Rocky Mountains, and a prairie cropland/grassland site (Kenaston). The Canadian Land Surface Scheme 3.6 (CLASS) was used for modelling. The Global Environmental Multiscale (GEM) model with Canadian Precipitation Analysis (CaPA) was also used as forcing. There was good agreement between observed meteorology and GEM/CaPA, though some deficiencies in GEM/CaPA were identified: the effects of sub-grid topography on incoming radiation and wind speed were not accounted for at MCRB, and CaPA did not capture some convective rainfall events at Kenaston. CLASS simulations using both sets of forcing showed difficulties in simulating snow depth, soil moisture and evapotranspiration; certain difficulties were linked to GEM/CaPA deficiencies and/or CLASS. Both sets of forcing tended to overestimate the duration of snow cover at MCRB, but during different years. With GEM/CaPA as forcing, CLASS overestimated the duration of frozen soils. The GEM/CaPA precipitation difficulties at Kenaston degraded soil moisture simulations.
EDITOR A. Castellarin; ASSOCIATE EDITOR E. Volpi 相似文献
20.
Statistical Postprocessing of NWP Model Outputs Applied to Maximum and Minimum Temperature Forecasts
Karel Dejmal 《Studia Geophysica et Geodaetica》2000,44(1):73-83
Statistical postprocessing of NWP model outputs is applied to maximum and minimum temperature forecasts. Two approaches to its application are effected to local short-range weather forecasts of minimum and maximum temperatures: Model Output Statistics and modified Perfect Prognosis. The modified Perfect Prognosis method is restricted to the first step of PP because of the significant difference between the horizontal resolution of the available objective analyses and the NWP model outputs. The modified Perfect Prognosis method uses actual data from the objective analysis related to the forecast period instead of the NWP forecast. The results are compared with a simple statistical prognostic model, which does not utilize the NWP model outputs, and with simple reference methods. The forecast is verified using ground station measurements from stations providing SYNOP reports. The results show that the predictive accuracy of the Model Output Statistics method is not very different from that of the modified Perfect Prognosis method, and both are significantly more accurate than the direct predictions of the NWP model. The results have confirmed that statistical postprocessing is able to make localized predictions even if lowresolution data are used. 相似文献