Advanced Search

2013 Vol. 30, No. 5

Display Method:
Ensemble Data Assimilation in a Simple Coupled Climate Model: The Role of Ocean-Atmosphere Interaction
LIU Zhengyu, WU Shu, ZHANG Shaoqing, LIU Yun, RONG Xinyao
2013, 30(5): 1235-1248. doi: 10.1007/s00376-013-2268-z
A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere.
A Forecast Error Correction Method in Numerical Weather Prediction by Using Recent Multiple-time Evolution Data
XUE Hai-Le, SHEN Xue-Shun, CHOU Ji-Fan
2013, 30(5): 1249-1259. doi: 10.1007/s00376-013-2274-1
The initial value error and the imperfect numerical model are usually considered as error sources of numerical weather prediction (NWP). By using past multi-time observations and model output, this study proposes a method to estimate imperfect numerical model error. This method can be inversely estimated through expressing the model error as a Lagrange interpolation polynomial, while the coefficients of polynomial are determined by past model performance. However, for practical application in the full NWP model, it is necessary to determine the following criteria: (1) the length of past data sufficient for estimation of the model errors, (2) a proper method of estimating the term model integration with the exact solution when solving the inverse problem, and (3) the extent to which this scheme is sensitive to the observational errors. In this study, such issues are resolved using a simple linear model, and an advection-diffusion model is applied to discuss the sensitivity of the method to an artificial error source. The results indicate that the forecast errors can be largely reduced using the proposed method if the proper length of past data is chosen. To address the three problems, it is determined that (1) a few data limited by the order of the corrector can be used, (2) trapezoidal approximation can be employed to estimate the term in this study; however, a more accurate method should be explored for an operational NWP model, and (3) the correction is sensitive to observational error.
Technical Note on a Track-pattern-based Model for Predicting Seasonal Tropical Cyclone Activity over the Western North Pacific
Chang-Hoi HO, Joo-Hong KIM, Hyeong-Seog KIM, Woosuk CHOI, Min-Hee LEE, Hee-Dong YOO, Tae-Ryong KIM, Sangwook PARK
2013, 30(5): 1260-1274. doi: 10.1007/s00376-013-2237-6
Recently, the National Typhoon Center (NTC) at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone (TC) track density from June to October. This model is the first approach to target seasonal TC track clusters covering the entire western North Pacific (WNP) basin, and may represent a milestone for seasonal TC forecasting, using a simple statistical method that can be applied at weather operation centers. In this note, we describe the procedure of the track-pattern-based model with brief technical background to provide practical information on the use and operation of the model. The model comprises three major steps. First, long-term data of WNP TC tracks reveal seven climatological track clusters. Second, the TC counts for each cluster are predicted using a hybrid statistical-dynamical method, using the seasonal prediction of large-scale environments. Third, the final forecast map of track density is constructed by merging the spatial probabilities of the seven clusters and applying necessary bias corrections. Although the model is developed to issue the seasonal forecast in mid-May, it can be applied to alternative dates and target seasons following the procedure described in this note. Work continues on establishing an automatic system for this model at the NTC.
Relationship between Cloud Characteristics and Radar Reflectivity Based on Aircraft and Cloud Radar Co-observations
ZONG Rong, LIU Liping, YIN Yan
2013, 30(5): 1275-1286. doi: 10.1007/s00376-013-2090-7
Cloud properties were investigated based on aircraft and cloud radar co-observation conducted at Yitong, Jilin, Northeast China. The aircraft provided in situmeasurements of cloud droplet size distribution, while the millimeter-wavelength cloud radar vertically scanned the same cloud that the aircraft penetrated. The reflectivity factor calculated from aircraft measurements was compared in detail with simultaneous radar observations. The results showed that the two reflectivities were comparable in warm clouds, but in ice cloud there were more differences, which were probably associated with the occurrence of liquid water. The acceptable agreement between reflectivities obtained in water cloud confirmed that it is feasible to derive cloud properties by using aircraft data, and hence for cloud radar to remotely sense cloud properties. Based on the dataset collected in warm clouds, the threshold of reflectivity to diagnose drizzle and cloud particles was studied by analyses of the probability distribution function of reflectivity from cloud particles and drizzle drops. The relationship between reflectivity factor (Z) and cloud liquid water content (LWC) was also derived from data on both cloud particles and drizzle. In comparison with cloud droplets, the relationship for drizzle was blurred by many scatter points and thus was less evident. However, these scatters could be partly removed by filtering out the drop size distribution with a large ratio of reflectivity and large extinction coefficient but small effective radius. Empirical relationships of Z-LWC for both cloud particles and drizzle could then be derived.
Effect of Doubling the Ensemble Size on the Performance of Ensemble Prediction in the Warm Season Using MOGREPS Implemented at the KMA
Jun Kyung KAY, Hyun Mee KIM, Young-Youn PARK, Joohyung SON
2013, 30(5): 1287-1302. doi: 10.1007/s00376-012-2083-y
Using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) implemented at the Korea Meteorological Administration (KMA), the effect of doubling the ensemble size on the performance of ensemble prediction in the warm season was evaluated. Because a finite ensemble size causes sampling error in the full forecast probability distribution function (PDF), ensemble size is closely related to the efficiency of the ensemble prediction system. Prediction capability according to doubling the ensemble size was evaluated by increasing the number of ensembles from 24 to 48 in MOGREPS implemented at the KMA. The initial analysis perturbations generated by the Ensemble Transform Kalman Filter (ETKF) were integrated for 10 days from 22 May to 23 June 2009. Several statistical verification scores were used to measure the accuracy, reliability, and resolution of ensemble probabilistic forecasts for 24 and 48 ensemble member forecasts. Even though the results were not significant, the accuracy of ensemble prediction improved slightly as ensemble size increased, especially for longer forecast times in the Northern Hemisphere. While increasing the number of ensemble members resulted in a slight improvement in resolution as forecast time increased, inconsistent results were obtained for the scores assessing the reliability of ensemble prediction. The overall performance of ensemble prediction in terms of accuracy, resolution, and reliability increased slightly with ensemble size, especially for longer forecast times.
Using Analysis State to Construct a Forecast Error Covariance Matrix in Ensemble Kalman Filter Assimilation
ZHENG Xiaogu, WU Guocan, ZHANG Shupeng, LIANG Xiao, DAI Yongjiu, LI Yong
2013, 30(5): 1303-1312. doi: 10.1007/s00376-012-2133-5
Correctly estimating the forecast error covariance matrix is a key step in any data assimilation scheme. If it is not correctly estimated, the assimilated states could be far from the true states. A popular method to address this problem is error covariance matrix inflation. That is, to multiply the forecast error covariance matrix by an appropriate factor. In this paper, analysis states are used to construct the forecast error covariance matrix and an adaptive estimation procedure associated with the error covariance matrix inflation technique is developed. The proposed assimilation scheme was tested on the Lorenz-96 model and 2D Shallow Water Equation model, both of which are associated with spatially correlated observational systems. The experiments showed that by introducing the proposed structure of the forecast error covariance matrix and applying its adaptive estimation procedure, the assimilation results were further improved.
Analytical Studies of the Cloud Droplet Spectral Dispersion Influence on the First Indirect Aerosol Effect
XIE Xiaoning, LIU Xiaodong
2013, 30(5): 1313-1319. doi: 10.1007/s00376-012-2141-5
Atmospheric aerosols (acting as cloud condensation nuclei) can enhance the cloud droplet number concentration and reduce the cloud droplet size, and in turn affect the cloud optical depth, as well as the cloud albedo, and thereby exert a radiative influence on climate (the first indirect aerosol effect). In this paper, based on various relationships between cloud droplet spectral dispersion () and cloud droplet number concentration (Nc), we analytically derive the corresponding expressions of the cloud radiative forcing induced by changes in the cloud droplet number concentration. Further quantitative evaluation indicates that the cloud radiative forcing induced by aerosols for the different- Nc relationships varies from - 29.1% to 25.2%, compared to the case without considering spectral dispersion (=0). Our results suggest that an accurate description of -Nc relationships helps to reduce the uncertainty of the first indirect aerosol effect and advances our scientific understanding of aerosol-cloud-radiation interactions.
An Accurate Multimoment Constrained Finite Volume Transport Model on Yin-Yang Grids
LI Xingliang, SHEN Xueshun, PENG Xindong, XIAO Feng, ZHUANG Zhaorong, CHEN Chungang
2013, 30(5): 1320-1330. doi: 10.1007/s00376-013-2217-x
A global transport model is proposed in which a multimoment constrained finite volume (MCV) scheme is applied to a Yin-Yang overset grid. The MCV scheme defines 16 degrees of freedom (DOFs) within each element to build a 2D cubic reconstruction polynomial. The time evolution equations for DOFs are derived from constraint conditions on moments of line-integrated averages (LIA), point values (PV), and values of first-order derivatives (DV). The Yin-Yang grid eliminates polar singularities and results in a quasi-uniform mesh. A limiting projection is designed to remove nonphysical oscillations around discontinuities. Our model was tested against widely used benchmarks; the competitive results reveal that the model is accurate and promising for developing general circulation models.
Performances of Seven Datasets in Presenting the Upper Ocean Heat Content in the South China Sea
CHEN Xiao, YAN Youfang, CHENG Xuhua, QI Yiquan
2013, 30(5): 1331-1342. doi: 10.1007/s00376-013-2132-1
In this study, the upper ocean heat content (OHC) variations in the South China Sea (SCS) during 1993-2006 were investigated by examining ocean temperatures in seven datasets, including World Ocean Atlas 2009 (WOA09) (climatology), Ishii datasets, Ocean General Circulation Model for the Earth Simulator (OFES), Simple Ocean Data Assimilation system (SODA), Global Ocean Data Assimilation System (GODAS), China Oceanic ReAnalysis system (CORA), and an ocean reanalysis dataset for the joining area of Asia and Indian-Pacific Ocean (AIPO1.0). Among these datasets, two were independent of any numerical model, four relied on data assimilation, and one was generated without any data assimilation. The annual cycles revealed by the seven datasets were similar, but the interannual variations were different. Vertical structures of temperatures along the 18N, 12.75N, and 120E sections were compared with data collected during open cruises in 1998 and 2005-08. The results indicated that Ishii, OFES, CORA, and AIPO1.0 were more consistent with the observations. Through systematic comparisons, we found that each dataset had its own shortcomings and advantages in presenting the upper OHC in the SCS.
Statistical Guidance on Seasonal Forecast of Korean Dust Days over South Korea in the Springtime
Keon Tae SOHN
2013, 30(5): 1343-1352. doi: 10.1007/s00376-012-2112-x
This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast (below normal, normal, above normal) which was classified based on the mean and the standard deviation of Korean dust days for a period of 30 years (1981-2010). In this study, we used three kinds of monthly data: the Korean dust days observed in South Korea, the National Center for Environmental Prediction in National Center for Atmospheric Research (NCEP/NCAR) reanalysis data for meteorological factors over source regions of Asian dust, and the large-scale climate indices offered from the Climate Diagnostic Center and Climate Prediction Center in NOAA. Forecast guidance consisted of two components; ordinal logistic regression model to generate trinomial distributions, and conversion algorithm to generate ternary forecast by two thresholds. Forecast guidance was proposed for each month separately and its predictability was evaluated based on skill scores.
Numerical Simulation of the Sudden Rainstorm Associated with the Remnants of Typhoon Meranti (2010)
ZHOU Lingli, DU Huiliang, ZHAI Guoqing, WANG Donghai
2013, 30(5): 1353-1372. doi: 10.1007/s00376-012-2127-3
The Advanced Research Weather Forecasting (ARW) model was used to simulate the sudden heavy rainstorm associated with the remnants of Typhoon Meranti in September 2010. The results showed that the heavy rainfall was produced when the remnant clouds redeveloped suddenly, and the redevelopment was caused by rapid growth of micro/mesoscale convective systems (MCSs). As cold air intruded into the warm remnant clouds, the atmosphere became convectively unstable and frontogenesis happened due to strong wind shear between weak northerly flow and strong southwesterly flow in the lower levels. Under frontogenesis-forcing and warm-air advection stimulation in updrafts, vertical convection developed intensely inside the remnant clouds, with MCSs forming and maturing along the front. The genesis and development of MCSs was due to the great progress vertical vorticity made. The moist isentropic surface became slantwise as atmospheric baroclinity intensified when cold air intruded, which reduced the convective instability of the air.Meanwhile, vertical wind shear increased because the north cold air caused the wind direction to turn from south to north with height. In accordance with slantwise vorticity development (SVD), vertical vorticity would develop vigorously and contribute greatly to MCSs. Buoyancy, the pressure gradient, and the lifting of cold air were collectively the source of kinetic energy for rainfall. The low-level southwesterly jet from the western margin of the Western Pacific Subtropical High transported water and heat to remnant clouds. Energy bursts and continuous water vapor transportation played a major role in producing intense rainfall in a very short period of time.
Effect of Implementing Ecosystem Functional Type Data in a Mesoscale Climate Model
2013, 30(5): 1373-1386. doi: 10.1007/s00376-012-2143-3
In this paper, we introduce a new concept of land-surface state representation for southern South America, which is based on functional attributes of vegetation, and implement a new land-cover (Ecosystem Functional Type, hereafter EFT) dataset in the Weather and Research Forecasting (WRF) model. We found that the EFT data enabled us to deal with functional attributes of vegetation and time-variant features more easily than the default land-cover data in the WRF. In order to explore the usefulness of the EFT data in simulations of surface and atmospheric variables, numerical simulations of the WRF model, using both the US Geological Survey (USGS) and the EFT data, were conducted over the La Plata Basin in South America for the austral spring of 1998 and compared with observations. Results showed that the model simulations were sensitive to the lower boundary conditions and that the use of the EFT data improved the climate sim-ulation of 2-m temperature and precipitation, implying the need for this type of information to be included in numerical climate models.
The Impact of Ecosystem Functional Type Changes on the La Plata Basin Climate
2013, 30(5): 1387-1405. doi: 10.1007/s00376-012-2149-x
In this paper, the effects of land cover changes on the climate of the La Plata Basin in southern South America are investigated using the Weather and Research Forecasting (WRF) Model configured on a 30/10-km two-way interactive nested grid. To assess the regional climate changes resulting from land surface changes, the standard land cover types are replaced by time-varying Ecosystem Functional Types (EFTs), which is a newly devised land-cover classification that characterizes the spatial and interannual variability of surface vegetation dynamics. These variations indicate that natural and anthropogenic activities have caused changes in the surface physical parameters of the basin, such as albedo and roughness length, that contributed to regional climate changes. EFTs are obtained from functional attributes of vegetation computed from properties of the Normalized Difference Vegetation Index (NDVI) to represent patches of the land surface with homogeneous energy and gas exchanges with the atmosphere. Four simulations are conducted, each experimental period ranging from September to November in two contrasting years, 1988 and 1998. The influence of an identical EFT change on the surface heat fluxes, 2-m temperature and humidity, 10-m winds, convective instabilities and large-scale moisture fluxes and precipitation are explored for 1988 (a dry year) and 1998 (a wet year). Results show that the surface and atmospheric climate has a larger response to the same EFT changes in a dry year for 2-m temperature and 10-m wind; the response is larger in a wet year for 2-m water vapor mixing ratio, convective available potential energy, vertically integrated moisture fluxes and surface precipitation. For EFTs with high productivity and a weak seasonal cycle, the near-surface temperature during the spring of 1988 and 1998 increased by as much as 1C in the central and western portions of La Plata Basin. Additionally, for higher productivity EFTs, precipitation differences were generally positive in both dry and wet years, although the patterns are not uniform and exhibit certain patchiness with drier conditions.
Dynamic Analogue Initialization for Ensemble Forecasting
LI Shan, RONG Xingyao, LIU Yun, LIU Zhengyu, Klaus FRAEDRICH
2013, 30(5): 1406-1420. doi: 10.1007/s00376-012-2244-z
This paper introduces a new approach for the initialization of ensemble numerical forecasting: Dynamic Analogue Initialization (DAI). DAI assumes that the best model state trajectories for the past provide the initial conditions for the best forecasts in the future. As such, DAI performs the ensemble forecast using the best analogues from a full size ensemble. As a pilot study, the Lorenz63 and Lorenz96 models were used to test DAI's effectiveness independently. Results showed that DAI can improve the forecast significantly. Especially in lower-dimensional systems, DAI can reduce the forecast RMSE by ~50% compared to the Monte Carlo forecast (MC). This improvement is because DAI is able to recognize the direction of the analysis error through the embedding process and therefore selects those good trajectories with reduced initial error. Meanwhile, a potential improvement of DAI is also proposed, and that is to find the optimal range of embedding time based on the error's growing speed.
Impacts of Snow Cover on Vegetation Phenology in the Arctic from Satellite Data
ZENG Heqing, JIA Gensuo
2013, 30(5): 1421-1432. doi: 10.1007/s00376-012-2173-x
The dynamics of snow cover is considered an essential factor in phenological changes in Arctic tundra and other northern biomes. The Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra satellite data were selected to monitor the spatial and temporal heterogeneity of vegetation phenology and the timing of snow cover in western Arctic Russia (the Yamal Peninsula) during the period 2000-10. The magnitude of changes in vegetation phenology and the timing of snow cover were highly heterogeneous across latitudinal gradients and vegetation types in western Arctic Russia. There were identical latitudinal gradients for start of season (SOS) (r2=0.982, p0.0001), end of season (EOS) (r2=0.938, p0.0001), and last day of snow cover (LSC) (r2=0.984, p0.0001), while slightly weaker relationships between latitudinal gradients and first day of snow cover (FSC) were observed (r2=0.48, p0.0042). Delayed SOS and FSC, and advanced EOS and LSC were found in the south of the region, while there were completely different shifts in the north. SOS for the various land cover features responded to snow cover differently, while EOS among different vegetation types responded to snowfall almost the same. The timing of snow cover is likely a key driving factor behind the dynamics of vegetation phenology over the Arctic tundra. The present study suggests that snow cover urgently needs more attention to advance understanding of vegetation phenology in the future.
A Numerical Study on the Effect of an Extratropical Cyclone on the Evolution of a Midlatitude Front
CHEN Guanghua
2013, 30(5): 1433-1448. doi: 10.1007/s00376-012-2191-8
The extratropical transition (ET) of tropical cyclone (TC) Haima (2004) was simulated to understand the impact of TC on midlatitude frontal systems. Two experiments were conducted using the Advanced Research version of the Weather Research and Forecast (WRF) model. In the control run (CTL), a vortex was extracted from the 24-hour pre-run output and then inserted into the National Centers for Environmental Prediction (NCEP) global final (FNL) analysis as an initial condition, while TC circulation was removed from the initial conditions in the sensitivity run (NOTC). Comparisons of the experiments demonstrate that the midlatitude front has a wider meridional extent in the NOTC run than that in the CTL run. Furthermore, the CTL run produces convection suppression to the southern side of the front due to strong cold advection related to the TC circulation. The easterly flow north of the TC not only decelerates the eastward displacement of the front and contracts its zonal scale but also transports more moisture westward and lifts the air along equivalent potential temperature surfaces ahead of the front. As a result, the ascending motion and diabatic heating are enhanced in the northeastern edge of the front, and the anticyclonic outflow in the upper-level is intensified. The increased pressure gradient and divergent flow aloft strengthen the upper-level jet and distort the trough axis in a northwest-southeast orientation. The thermal contrast between the two systems and the dynamic contribution related to the TC circulation can facilitate scalar and rotational frontogenesis to modulate the frontal structure.
Impact of Rain Snow Threshold Temperature on Snow Depth Simulation in Land Surface and Regional Atmospheric Models
WEN Lijuan, Nidhi NAGABHATLA, Lü Shihua, Shih-Yu WANG
2013, 30(5): 1449-1460. doi: 10.1007/s00376-012-2192-7
This study investigates the impact of rain snow threshold (RST) temperatures on snow depth simulation using the Community Land Model (CLM) and the Weather Research and Forecasting model (WRF-coupled with the CLM and hereafter referred to as WRF_CLM), and the difference in impacts. Simulations were performed from 17 December 1994 to 30 May 1995 in the French Alps. Results showed that both the CLM and the WRF_CLM were able to represent a fair simulation of snow depth with actual terrain height and 2.5℃ RST temperature. When six RST methods were applied to the simulation using WRF_CLM, the simulated snow depth was the closest to observations using 2.5℃ RST temperature, followed by that with Pipes', USACE, Kienzle's, Dai's, and 0℃ RST temperature methods. In the case of using CLM, simulated snow depth was the closest to the observation with Dai's method, followed by with USACE, Pipes', 2.5℃ RST temperature, Kienzle's, and 0℃ RST temperature method. The snow depth simulation using the WRF_CLM was comparatively sensitive to changes in RST temperatures, because the RST temperature was not only the factor to partition snow and rainfall. In addition, the simulated snow related to RST temperature could induce a significant feedback by influencing the meteorological variables forcing the land surface model in WRF_CLM. In comparison, the above variables did not change with changes in RST in CLM. Impacts of RST temperatures on snow depth simulation could also be influenced by the patterns of temperature and precipitation, spatial resolution, and input terrain heights.
Characteristics of Sea Breeze Front Development with Various Synoptic Conditions and Its Impact on Lower Troposphere Ozone Formation
Hyo-Eun JI, Soon-Hwan LEE, Hwa-Woon LEE
2013, 30(5): 1461-1478. doi: 10.1007/s00376-013-2256-3
To examine the correlation between the sizes of sea breeze fronts and pollutants under the influence of synoptic fields, a numerical simulation was conducted in the southeast coastal area of the Korean Peninsula, where relatively high concentrations of pollutants occur because of the presence of various kinds of industrial developments. Sea breeze and sea breeze front days during the period 2005-09 were identified using wind profiler data and, according to the results, the number of days were 72 and 53, respectively. When synoptic forcing was weak, sea breeze fronts moved fast both in horizontal fields and in terms of wind velocity, while in the case of strong synoptic forcing, sea breeze fronts remained at the coast or moved slowly due to strong opposing flows. In this case, the sea breeze front development function and horizontal potential temperature difference were larger than with weak synoptic forcing. The ozone concentration that moves together with sea breeze fronts was also formed along the frontal surfaces. Ozone advection and diffusion in the case of strong synoptic forcing was suppressed at the frontal surface and the concentration gradient was large. The vertical distribution of ozone was very low due to the Thermal Internal Boundary Layer (TIBL) being low.
Regional Estimates of Evapotranspiration over Northern China Using a Remote-sensing-based Triangle Interpolation Method
WANG Hesong, JIA Gensuo
2013, 30(5): 1479-1490. doi: 10.1007/s00376-013-2294-x
Regional estimates of evapotranspiration (ET) are critical for a wide range of applications. Satellite remote sensing is a promising tool for obtaining reasonable ET spatial distribution data. However, there are at least two major problems that exist in the regional estimation of ET from remote sensing data. One is the conflicting requirements of simple data over a wide region, and accuracy of those data. The second is the lack of regional ET products that cover the entire region of northern China. In this study, we first retrieved the evaporative fraction (EF) by interpolating from the difference of day/night land surface temperature (T) and the normalized difference vegetation index (NDVI) triangular-shaped scatter space. Then, ET was generated from EF and land surface meteorological data. The estimated eight-day EF and ET results were validated with 14 eddy covariance (EC) flux measurements in the growing season (July-September) for the year 2008 over the study area. The estimated values agreed well with flux tower measurements, and this agreement was highly statistically significant for both EF and ET (p0.01), with the correlation coefficient for EF (R2=0.64) being relatively higher than for ET (R2=0.57). Validation with EC-measured ET showed the mean RMSE and bias were 0.78 mm d-1 (22.03 W m-2) and 0.31 mm d-1 (8.86 W m-2), respectively. The ET over the study area increased along a clear longitudinal gradient, which was probably controlled by the gradient of precipitation, green vegetation fractions, and the intensity of human activities. The satellite-based estimates adequately captured the spatial and seasonal structure of ET. Overall, our results demonstrate the potential of this simple but practical method for monitoring ET over regions with heterogeneous surface areas.
ENSO Indices and Analyses
WANG Zhiren, WU Dexing, CHEN Xue'en, QIAO Ran
2013, 30(5): 1491-1506. doi: 10.1007/s00376-012-2238-x
New ENSO indices were developed and the spatial variability and temporal evolution of ENSO were analyzed based on the new indices and modeling experiments, as well as multiple data resources. The new indices, after being defined, were validated with their good diagnostic characteristics and correlation with wind and SST. In the analysis after the definition and validation of the new indices, ENSO feedbacks from wind, heat fluxes, and precipitation were spatially and temporally examined in order to understand ENSO variability and evolution with some emphasized points such as the interaction among the feedbacks, the role of westerly wind bursts and the transformation between zonal and meridional circulations in an ENSO cycle, and the typical pattern of modern ENSO.