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1.
The performance of separate bias Kalman filter (SepKF) in correcting the model bias for the improvement of soil moisture profiles is evaluated by assimilating the near-surface soil moisture observations into a land surface model (LSM). First, an observing system simulation experiment (OSSE) is carried out, where the true soil moisture is known, two types of model bias (i.e., constant and sinusoidal) are specified, and the bias error covariance matrix is assumed to be proportional to the model forecast error covariance matrix with a ratio λ. Second, a real assimilation experiment is carried out with measurements at a site over Northwest China. In the OSSE, the soil moisture estimation with the SepKF is improved compared with ensemble Kalman filter (EnKF) without the bias filter, because SepKF can properly correct the model bias, especially in the situation with a large model bias. However, the performance of SepKF becomes slightly worse if the constant model bias increases or temporal variability of the sinusoidal model bias becomes large. It is suggested that the ratio λ should be increased (decreased) in order to improve the soil moisture estimation if temporal variability of the sinusoidal model bias becomes high (low). Finally, the assimilation experiment with real observations also shows that SepKF can further improve the estimation of soil moisture profiles compared with EnKF without the bias correction.  相似文献   

2.
Information on the spatial and temporal pat- terns of surface carbon flux is crucial to understanding of source/sink mechanisms and projection of future atmospheric CO2 concentrations and climate. This study presents the construction and implementation of a terrestrial carbon cycle data assimilation system based on a dynamic vegetation and terrestrial carbon model Vegetation-Global-Atmosphere-Soil （VEGAS） with an advanced assimilation algorithm, the local ensemble transform Kalman filter （LETKF, hereafter LETKF-VEGAS）. An observing system simulation experiment （OSSE） framework was designed to evaluate the reliability of this system, and numerical experiments conducted by the OSSE using leaf area index （LAI） observations suggest that the LETKF -VEGAS can improve the estimations of leaf carbon pool and LAI significantly, with reduced root mean square errors and increased correlation coefficients with true values, as compared to a control run without assimilation. Furthermore, the LETKF-VEGAS has the potential to provide more accurate estimations of the net primary productivity （NPP） and carbon flux to atmosphere （CFta）.  相似文献   

3.
In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions （ff） in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data （1979-2008） from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System （GEOS）-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.  相似文献   

4.
The IAP/LASG GOALS coupled model is used to simulate the climate change during the 20th century using historical greenhouse gases concentrations, the mass mixing ratio of sulfate aerosols simulated by a CTM model, and reconstruction of solar variability spanning the period 1900 to 1997. Four simulations, including a control simulation and three forcing simulations, are conducted. Comparison with the observational record for the period indicates that the three forcing experiments simulate reasonable temporal and spatial distributions of the temperature change. The global warming during the 20th century is caused mainly by increasing greenhouse gas concentration especially since the late 1980s; sulfate aerosols offset a portion of the global warming and the reduction of global temperature is up to about 0.11℃ over the century; additionally, the effect of solar variability is not negligible in the simulation of climate change over the 20th century.  相似文献   

5.
The ensemble based forecast sensitivity to observation method by Liu and Kalnay is applied to the SPEEDY-LETKF system to estimate the observation impact of three types of simulated observations. The estimation results show that all types of observations have positive impact on short-range forecast. The largest impact in Northern Hemisphere is produced by rawinsondes, followed by satellite retrieved profiles and cloud drift wind data, which in Southern Hemisphere is produced by satellite retrieved profiles, rawinsondes and cloud drift wind data. Satellite retrieved profiles influence more on the Southern Hemisphere than on the Northern Hemisphere due to few observations from rawinsondes in the Southern Hemisphere. At the level of 200 to 300 hPa, the largest impact is attributed to wind observations from rawinsondes and cloud drift wind.  相似文献   

6.
Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impact weather events such as local severe storms(LSSs). High spectral resolution or hyperspectral infrared(HIR) sounders from geostationary orbit(GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE(Observing System Simulation Experiment)framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO(low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference(RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems(such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.  相似文献   

7.
There was a new concept of ‘adaptive or targeting observation’ in recent years, which is an additional and targeting observation based on the existing and fixed observing network for the atmosphere on the impacted region. Dropsonde is one of the important observing instruments in the adaptive or targeting observation. In this paper, GRAPES, the next generation of numerical weather prediction system of China has been used. The impacts on the typhoon Dujuan (No.200315) forecast in experiments with dropsonde have been studied and experiments on sensitivity have also been done. It was found that the forecasts of the elements have been improved obviously with the use of dropsonde, such as the path, the center location, and the intensity of typhoon. It was also found in the sensitivity studies that the setting of deviation structure also has obvious impacts on the forecast for typhoons. It is not true that the simulation is better when the proportion of the data of dropsonde is larger in the course to modify the background.  相似文献   

8.
Surface solar radiation(SSR) is a key component of the energy budget of the Earth’s surface, and it varies at different spatial and temporal scales. Considerable knowledge of how and why SSR varies is crucial to a better understanding of climate change, which surely requires long-term measurements of high quality. The objective of this study is to introduce a value-added SSR dataset from Oct 2004 to Oct 2019 based on measurements taken at Xianghe, a suburban site in the North China Plain; two va...  相似文献   

9.
This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through June 2003 including temperature data from the expendable bathythermographs （XBT）, thermistor data from the Tropical Ocean Global Atmosphere Tropical Atmosphere-Ocean （TOGA-TAO） mooring array, sea level anomalies from the Topex/Poseidon and Jason-1 altimetry （T/P-J）, and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography （ARGO） floats. An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments were carried out. The experiment that assimilated all four components of the observing system was taken as the reference. The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses in the off-equatorial region due to the large amount of measurements and high quality. Similarly, the impact of TAO is dominant in the equatorial region due to the focus of the spatial distribution. The Topex/Poseidon-Jason-1 can be highly complementary where the XBT and TAO observations are sparse. The contribution of XBT or TAO on the assimilated salinity is made by the model dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation syst  相似文献   

10.
This paper summarizes recent progress at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences in studies on targeted observations, data assimilation, and ensemble prediction, which are three effective strategies to reduce the prediction uncertainties and improve the forecast skill of weather and climate events. Considering the limitations of traditional targeted observation approaches, LASG researchers have developed a conditional nonlinear optimal perturbation-based targeted observation strategy to optimize the design of the observing network. This strategy has been employed to identify sensitive areas for targeted observations of the El Ni?o–Southern Oscillation, Indian Ocean dipole, and tropical cyclones, and has been demonstrated to be effective in improving the forecast skill of these events. To assimilate the targeted observations into the initial state of a numerical model, a dimension-reducedprojection-based four-dimensional variational data assimilation(DRP-4DVar) approach has been proposed and is used operationally to supply accurate initial conditions in numerical forecasts. The performance of DRP-4DVar is good, and its computational cost is much lower than the standard 4DVar approach. Besides, ensemble prediction,which is a practical approach to generate probabilistic forecasts of the future state of a particular system, can be used to reduce the prediction uncertainties of single forecasts by taking the ensemble mean of forecast members. In this field, LASG researchers have proposed an ensemble forecast method that uses nonlinear local Lyapunov vectors(NLLVs) to yield ensemble initial perturbations. Its application in simple models has shown that NLLVs are more useful than bred vectors and singular vectors in improving the skill of the ensemble forecast. Therefore, NLLVs represent a candidate for possible development as an ensemble method in operational forecasts. Despite the considerable efforts made towards developing these methods to reduce prediction uncertainties, much challenging but highly important work remains in terms of improving the methods to further increase the skill in forecasting such weather and climate events.  相似文献   

11.
In this paper the authors perform an extensive sensitivity analysis of the Indian summer monsoon rainfall to changes in parameters and boundary conditions which are influenced by human activities. For this study the authors use a box model of the Indian monsoon which reproduces key features of the observed monsoon dynamics such as the annual course of precipitation and the transitions between winter and summer regimes. Because of its transparency and computational efficiency, this model is highly suitable for exploring the effects of anthropogenic perturbations such as emissions of greenhouse gases and sulfur dioxide, and land cover changes, on the Indian monsoon. Results of a systematic sensitivity analysis indicate that changes in those parameters which are related to emissions of greenhouse gases lead to an increase in Indian summer rainfall. In contrast, all parameters related to higher atmospheric aerosol concentrations lead to a decrease in Indian rainfall. Similarly, changes in parameters which can be related to forest conversion or desertifieation, act to decrease the summer precipitation. The results indicate that the sign of precipitation changes over India will be dependent on the direction and relative magnitude of different human perturbations.  相似文献   

12.
Min WEI 《大气科学进展》2005,22(6):798-806
The Asian summer monsoon is an important part of the climate system. Investigating the response of the Asian summer monsoon to changing concentrations of greenhouse gases and aerosols will be meaningful to understand and predict climate variability and climate change not only in Asia but also globally. In order to diagnose the impacts of future anthropogenic emissions on monsoon climates, a coupled general circulation model of the atmosphere and the ocean has been used at the Max-Planck-Institute for Meteorology. In addition to carbon dioxide, the major well mixed greenhouse gases such as methane, nitrous oxide, several chlorofluorocarbons, and CFC substitute gases are prescribed as a function of time. The sulfur cycle is simulated interactively, and both the direct aerosol effect and the indirect cloud albedo effect are considered. Furthermore, changes in tropospheric ozone have been pre-calculated with a chemical transport model and prescribed as a function of time and space in the climate simulations. Concentrations of greenhouse gases and anthropogenic emissions of sulfur dioxide are prescribed according to observations （1860-1990） and projected into the future （1990-2100） according to the Scenarios A2 and B2 in Special Report on Emissions Scenarios （SRES, Nakcenovic et al., 2000） developed by the Intergovernmental Panel on Climate Change （IPCC）. It is found that the Indian summer monsoon is enhanced in the scenarios in terms of both mean precipitation and interannual variability. An increase in precipitation is simulated for northern China but a decrease for the southern part. Furthermore, the simulated future increase in monsoon variability seems to be linked to enhanced ENSO variability towards the end of the scenario integrations.  相似文献   

13.
A New Algorithm for Sea Fog／Stratus Detection Using GMS-5 IR Data   总被引：7，自引：0，他引：7  
A new algorithm for the detection of fog/stratus over the ocean from the GMS-5 infrared (IR) channel data is presented. The new algorithm uses a clear-sky radiance composite map (CSCM) to compare the hourly observations of the IR radiance. The feasibility of the simple comparison is justified by the theoretical simulations of the fog effect on the measured radiance using a radiative transfer model. The simulation results show that the presence of fog can be detected provided the visibility is worse than 1 km and the background clear-sky radiances are accurate enough with known uncertainties. For the current study, an accurate CSCM is constructed using a modified spatial and temporal coherence method, which takes advantage of the high temporal resolution of the GMS-5 observations. The new algorithm is applied for the period of 10-12 May 1999, when heavy sea fog formed near the southwest coast of the Korean Peninsula. Comparisons of the fog/stratus index, defined as the difference between the measured and clear-sky brightness temperature, from the new algorithm to the results from other methods, such as the dual channel difference of NOAA/AVHRR and the earth albedo method, show a good agreement. The fog/stratus index also compares favorably with the ground observations of visibility and relative humidity. The general characteristics of the fog/stratus index and visibility are relatively well matched, although the relationship among the absolute values, the fog/stratus index, visibility, and relative humidity, varies with time. This variation is thought to be due to the variation of the atmospheric conditions and the characteristics of fog/stratus, which affect the derived fog/stratus index.  相似文献   

14.
Methane （CH4） emissions estimated with the Intergovernmental Panel on Climate Change （IPCC） inventory method at the city and regional scale are subject to large uncertainties.In this study,we determined the CH4：CO2 emissions ratio for both Nanjing and the Yangtze River Delta （YRD）,using the atmospheric CH4 and CO2 concentrations measured at a suburban site in Nanjing in the winter.The atmospheric estimate of the CH4：CO2 emissions ratio was in reasonable agreement with that calculated using the IPCC method for the YRD （within 20％）,but was 200％ greater for the municipality of Nanjing.The most likely reason for the discrepancy is that emissions from unmanaged landfills are omitted from the official statistics on garbage production.  相似文献   

15.
A new spatial consistency quality control method (SRF) based on the spatial regression test (SRT) and random forest (RF) was adapted to identify potential outliers in daily surface temperature observations in this article. For the new method, the SRT method was used to filter the data and the RF method was used to conduct regression. To evaluate the performance of the quality control method, the SRF, SRT and RF methods were applied to a surface temperature dataset with seeded errors from different regions of China from 2005 to 2014. Compared to SRT and RF, the results indicate that the SRF method outperforms the other two methods for the most cases. And the results of the comparison led to the recommendation that the SRF method improves the regression accuracy of traditional spatial consistency quality control methods and reduces the runtime of random forest through data refinement.  相似文献   

16.
Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP)models.As observations are expensive and logistically challenging,it is important to evaluate the benefit that additional observations could bring to NWP.Atmospheric soundings applying unmanned aerial vehicles(UAVs)have a large potential to supplement conventional radiosonde sounding observations.Here,we applied UAV and radiosonde sounding observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting(Polar WRF)model.Our experiments revealed small to moderate impacts of radiosonde and UAV data assimilation.In any case,the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature,wind speed,and humidity at the observation site for most of the time.Further,the impact on the results of 5-day-long Polar WRF experiments was often felt over distances of at least 300 km from the observation site.All experiments succeeded in capturing the main features of the evolution of near-surface variables,but the effects of data assimilation varied between different cases.Due to the limited vertical extent of the UAV observations,the impact of their assimilation was limited to the lowermost 1?2-km layer,and assimilation of radiosonde data was more beneficial for modeled sea level pressure and near-surface wind speed.  相似文献   

17.
A relatively independent and small-scale heavy rainfall event occurred to the south of a slow eastward-moving meso-α-scale vortex. The analysis shows that a meso-β-scale system is heavily responsible for the intense precipitation. An attempt to simulate it met with some failures. In view of its small scale, short lifetime and relatively sparse observations at the initial time, an adjoint model was used to examine the sensitivity of the meso-β-scale vortex simulation with respect to initial conditions. The adjoint sensitivity indicates how small perturbations of initial model variables anywhere in the model domain can influence the central vorticity of the vortex. The largest sensitivity for both the wind and temperature perturbation is located below 700 hPa, especially at the low level. The largest sensitivity for the water vapor perturbation is located below 500 hPa, especially at the middle and low levels. The horizontal adjoint sensitivity for all variables is mainly located toward the upper reaches of the Yangtze River with respect to the simulated meso-β-scale system in Hunan and Jiangxi provinces with strong locality. The sensitivity shows that warm cyclonic perturbations in the upper reaches can have a great effect on the development of the meso-β-scale vortex. Based on adjoint sensitivity, forward sensitivity experiments were conducted to identify factors influencing the development of the meso-β-scale vortex and to explore ways of improving the prediction. A realistic prediction was achieved by using adjoint sensitivity to modify the initial conditions and implanting a warm cyclone at the initial time in the upper reaches of the river with respect to the meso-β-scale vortex,as is commonly done in tropical cyclone prediction.  相似文献   

18.
郭准  周天军 《大气科学进展》2013,30(6):1758-1770
To understand the strengths and limitations of a low-resolution version of Flexible Global Ocean Atmosphere-Land-Sea-ice （FGOALS-gl） to simulate the climate of the last millennium, the energy balance, climate sensitivity and absorption feedback of the model are analyzed. Simulation of last-millennium climate was carried out by driving the model with natural （solar radiation and volcanic eruptions） and anthropogenic （greenhouse gases and aerosols） forcing agents. The model feedback factors for （model sensitivity to） different forcings were calculated. The results show that the system feedback factor is about 2.5 （W m-2） K-1 in the pre-industrial period, while 1.9 （W m-2） K-1 in the industrial era. Thus, the model＇s sensitivity to natural forcing is weak, which explains why it reproduces a weak Medieval Warm Period. The relatively reasonable simulation of the Little Ice Age is caused by both the specified radiative forcing and unforced linear cold drift. The model sensitivity in the industrial era is higher than that of the pre-industrial period. A negative net cloud radiative feedback operates during whole-millennial simulation and reduces the model＇s sensitivity to specified forcing. The negative net cloud radiative forcing feedback under natural forcing in the period prior to 1850 is due to the underestimation （overestimation） of the response of cloudiness （in-cloud water path）. In the industrial era, the strong tropospheric temperature response enlarges the effective radius of ice clouds and reduces the fractional ice content within cloud, resulting in a weak negative net cloud feedback in the industrial period. The water vapor feedback in the industrial era is also stronger than that in the pre-industrial period. Both are in favor of higher model sensitivity and thus a reasonable simulation of the 20th century global warming.  相似文献   

19.
Haze-to-fog transformation during a long lasting, low visibility episode was examined using the observations from a comprehensive field campaign conducted in Nanjing, China during 4-9 December 2013. In this episode, haze was transformed into fog and the fog lasted for dozens of hours. The impacts of meteorological factors such as wind, temperature (T) and relative humidity (RH) on haze, transition and fog during this episode were investigated. Results revealed significant differences between haze and fog days, due to their different formation mechanisms. Comparison was made for boundary-layer conditions during hazy days, haze-to-fog days and foggy days. Distributions of wind speed and wind direction as well as synoptic weather conditions around Nanjing had determinative impacts on the occurrences and characteristics of haze and fog. Weakened southerly wind in southern Nanjing resulted in high concentration of pollutants, and haze events occurred frequently during the study period. The wind speed was less than 1 m s-1 in the haze event, which resulted in a stable atmospheric condition and weak dispersion of the pollutants. The height of the temperature inversion was about 400 m during the period. The inversion intensity was weak and the temperature-difference was 4°C km-1 or less in haze, while the inversion was stronger, and temperature-difference was about 6°C km-1, approaching the inversion layer intensity in the fog event. Haze event is strongly influenced by ambient RH. RH values increased, which resulted in haze days evidently increased, suggesting that an increasing fraction of haze events be caused by hygroscopic growth of aerosols, rather than simply by high aerosol loading. When RH was above 90%, haze aerosols started to be transformed from haze to fog. This study calls for more efforts to control emissions to prevent haze events in the region.  相似文献   

20.
A regional chemical transport model, RAMS-CMAQ, was employed to assess the impacts of biosphere–atmosphere CO2 exchange on seasonal variations in atmospheric CO2 concentrations over East Asia. Simulated CO2 concentrations were compared with observations at 12 surface stations and the comparison showed they were generally in good agreement. Both observations and simulations suggested that surface CO2 over East Asia features a summertime trough due to biospheric absorption, while in some urban areas surface CO2 has a distinct summer peak, which could be attributed to the strong impact from anthropogenic emissions. Analysis of the model results indicated that biospheric fluxes and fossil-fuel emissions are comparably important in shaping spatial distributions of CO2 near the surface over East Asia. Biospheric flux plays an important role in the prevailing spatial pattern of CO2 enhancement and reduction on the synoptic scale due to the strong seasonality of biospheric CO2 flux. The elevation of CO2 levels by the biosphere during winter was found to be larger than 5ppm in North China and Southeast China, and during summertime a significant depletion( 7 ppm) occurred in most areas,except for the Indo-China Peninsula where positive bioflux values were found.  相似文献   

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