Numerical Simulation of Regional Short-Range Climate Anomalies

With the high-speed development of numerical weather prediction, since the later 1980's, the prediction of short-range climate anomalies has attracted worldwide meteorologists' attention . What the so called short-range refers to the time scale from one month to one season or more. In dealing with the problem of short-range climate prediction, two points are needed noticing: one is the basic research to explore or investigate the mechanism of variability of the slow varying components which mainly include internal dynamics of extratropics, external forcings and tropical dynamics, and the other is the modeling efforts to simulate the process of the long-term evolution of the signal which include the improvement of model quality, stochastic prediction and the air-sea-coupled model (Miyakoda et al.,1986). Previous researches on the numerical prediction of short-term climate anomalies are mostly concentrated in the analysis of variables with global spatial scale, especially the global general atmospheric circulation analysis.As to the simulation or prediction of regional short-term climate anomalies, there exist many difficulties and problems. Though some meteorologists are devoting themself to this field, up to now, they have not reached satisfactory results. As a primary effort, by using the 2-level general atmospheric circulation model developed in the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP-AGCM) (Zeng et al., 1989), and taking the year of 1985 as a case, a numerical simulation of regional short-term climate change is completed. We pay high attention to the predictant of anomalous summer rainfall in the Yangtze River and Yellow River valleys, especially its month to month variation.

A Numerical Study of the Mechanism for the Effect of Northern Winter Arctic Ice Cover on the Global Short-Range Climate Evolution

By using a nine-layer global spectral model involving fuller parameterization of physical processes, with a rhomboidal truncation at wavenumber 15, experiments are performed in terms of two numerical schemes, one with long-term mean coverage of Arctic ice (Exp.1), the other without the ice (Exp.2). Results indicate that the Arctic region is a heat source in Exp.2 relative to the case in Exp.1. Under the influence of the polar heat source simulated, there still exist stationary wavetrains that produce WA-EUP and weak PNA patterns in Northern winter. That either the Arctic or the tropical heat source can cause identical climatic effects is due to the fact that the anomaly of the Arctic ice cover will directly induce a south-propagating wavetrain, and bring about the redistribution of the tropical heat source / sink. The redistribution is responsible for new wavetrains that will exert impact on the global climate. The simulation results bear out further that the polar region in Exp.2 as a heat source, can produce, by local forcing, a pair of positive and negative difference centers, which circle the Arctic moving eastwards. Observed in the Northern Hemisphere extratropics is a 40-50 day oscillation in relation to the moving pair, both having the same period.

Study on Fog Climate Characteristic and Forecasting Method in East of Hexi Corridor

Using fog meteorological data of five stations of Wuwei in east of Hexi Corridor from 1961 to 2008,geography distribution and climate characteristic of fog were analyzed with statistical method.The results showed that fog had the obvious region characteristic,fog days were more in mountainous area than Sichuan area and were more in south than north.Fog assumed reducing tendency year by year.Fog occurring frequency was the highest from July to October in one year.Fog occurring centralized time was form 20:00 to next day 08:00 in one day.Selecting of ECMWF numerical forecast grid field,factor was initially elected with Press criterion,factor was selected with stepwise regression forecast method.The fog forecasting equation was built with optimal subset regression.The overall situation and the most superior significance equations of fog forecasting were ascertained finally for spring,summer and autumn.Fitting rate three seasonal forecasting equation were 85.5%,82.1% and 81.2% respectively,which would provide objective and effective instruction products for forecasting service.

Sea level change and forecast in the future — climate of the past,today and the future

The sea-level change is resulted from superposition of sun, moon and other planeries, and earth itself, biological process, atmosphere and oceanography, as well as artificial actions. As a result, the sea level change is really a sensitive integral variation value of many variations, or a combined function of coupling effects of various big systems. Therefore the above mentioned superposed action of different systems and the coupling effect of sun earth and biological aspects may be called as sun earth biological coupling effect system. Based on this hypothesis, the corresponding sun dynamic, air dynamic, water dynamic and earth dynamic conceptional models are established in order to research the multiple coupling effects and feedback machsnism between these big systems. In order to determine the relations, effectness and coherent relation of different variations, the quantity, analysis is conducted through collective variation and stage division. The quantity analysis indicates that the earths spindle rotation speed is the dynamic mechanism controlling the sea level change of fluctuation. The change rate of sea level in the world is ＋1.32 ＋ 0.22 mm/a, while the sea level change rate in China is only＋1.39 ＋ 0.26 mm/a in average. If take the CO2 content as the climate marker, eight cold stages （periods） are grouped out since two hundreds years AC. The extreme cold of the eighth cold stage started approximately at 1850 years AC. and if the stage from the extreme cold to extreme warm is determined as long as 200 years, the present ongoing warm stage will end at about 2050 years, there after the temperature will begin to tower. If the stage between cold and warm extremes lasts for 250 years, then the temperature will become lower at about 2100 year. Until to that time, the sea-level is estimated to raise ＋7 - ＋11 ＋ 3.5 cm again, and there after, the sea level will begin the new lowering trend. In the same time, the climate will enter into next new cold stage subsequently.

Impacts of Land Process on the Onset and Evolution of Asian Summer Monsoon in the NCEP Climate Forecast System

Impacts of land models and initial land conditions （ICs） on the Asian summer monsoon, especially its onset, were investigated using the NCEP Climate Forecast System （CFS）. Two land models, the Oregon State University （OSU） land model and the NCEP, OSU, Air Force, and Hydrologic Research Laboratory （Noah） land model, were used to get parallel experiments NCEP/Department of Energy （DOE） Global Reanalysis 2 System （GLDAS）. The experiments also used land ICs from the （GR2） and the Global Land Data Assimilation Previous studies have demonstrated that, a systematic weak bias appears in the modeled monsoon, and this bias may be related to a cold bias over the Asian land mass. Results of the current study show that replacement of the OSU land model by the Noah land model improved the model＇s cold bias and produced improved monsoon precipitation and circulation patterns. The CFS predicted monsoon with greater proficiency in E1 Nifio years, compared to La Nifia years model in monsoon predictions for individual years. and the Noah model performed better than the OSU These improvements occurred not only in relation to monsoon onset in late spring but also to monsoon intensity in summer. Our analysis of the monsoon features over the India peninsula, the Indo-China peninsula, and the South Chinese Sea indicates different degrees of improvement. Furthermore, a change in the land models led to more remarkable improvement in monsoon prediction than did a change from the GR2 land ICs to the GLDAS land ICs.

Analyzing and Forecasting Climate Change in Harbin City,Northeast China

Based on sounding data from 1975 to 2005 and TM/ETM+ remote sensing images in 1989, 2001 and 2007, the climate changes in Harbin City, Northeast China in recent 30 years were analyzed and forecasted. Results show that in the lower troposphere the meridional wind speed and mean annual wind speed decrease, and in the lower stratosphere the temperature decreases while the meridional wind speed increases significantly. In the study area, the climate is becoming warmer and wetter in the middle lower troposphere. The expansion of urban area has great effects on the surface air temperature and the wind speed, leading to the increase of the surface air temperature, the decrease of the surface wind speed, and the increase of the area of urban high temperature zone. The quantitative equations have been established among the surface air temperature, the carbon dioxide (CO2) concentration and the specific humidity (the water vapor content). It is predicted that the future increasing rate of the surface air temperature is 0.85℃/10yr if emission concentration of CO2 remains unchanged; if emission concentration of CO2 decreases to 75%, 50% and 25%, respectively, the surface air temperature will increase 0.65℃/10yr, 0.46℃/10yr and 0.27℃/10yr, respectively. The rise of the surface air temperature in the study area is higher than that of the global mean temperature forecasted by IPCC.

Climate and Forecast Mode Simulations for Antarctica:Implications for Temperature and Wind

Climate and forecast mode simulations with the regional climate model HIRlam-ECHAM（HIRHAM） are evaluated over a pan-Antarctic domain. The ability of the model to simulate temperature and wind profiles in the troposphere is quantified by comparing its results with radiosonde data acquired from the Davis station for January and July 2007. Compared to the climate mode, the forecast mode was found to deliver improved results for temperature and wind simulations at the near surface and in the lower troposphere. The main remaining model bias found was the under-representation of low-level wind jets. Based on ensemble simulations, it is shown that a distinct internal variability is inherent in the climate mode simulations, and associated areas of reduced predictability over Antarctica are identified.

Climate Features of Regional Fog in Liaoxi Area and Forecast Analysis

By using the fog data from 1995 to 2004 of four selected observation stations,the weather features of foggy days in Liaoxi area have been studied in this paper.The favorable surface and upper circulation for fog and its frequency have also been concluded from the statistic.In this paper,the forecasting index of fog,proposed on the basis of the condition and mechanism of the fog occurrence,has been tested by the 10-year analysis.Another test conducted by using the data of 1st July-31st December,2004 also gives a good result which has a vacancy rate of 22.2% and a miss rate of 5.1%.

APPLICATION EXPERIMENT OF ASSIMILATING RADAR-RETRIEVED WATER VAPOR IN SHORT-RANGE FORECAST OF RAINFALL IN THE ANNUALLY FIRST RAINY SEASON OVER SOUTH CHINA

A scheme of assimilating radar-retrieved water vapor is adopted to improve the quality of NWP initial field for improvement of the accuracy of short-range precipitation prediction. To reveal the impact of the assimilation of radar-retrieved water vapor on short-term precipitation forecast, three parallel experiments, cold start, hot start and hot start plus the assimilation of radar-retrieved water vapor, are designed to simulate the 31 days of May, 2013 with a fine numerical model for South China. Furthermore, a case of heavy rain that occurred from 8-9 May 2013 over the region from the southwest of Guangdong province to Pearl River Delta is analyzed in detail. Results show that the cold start experiment is not conducive to precipitation 12 hours ahead; the hot start experiment is able to reproduce well the first6 hours of precipitation, but badly for subsequent prediction; the experiment of assimilating radar-retrieved water vapor is not only able to simulate well the precipitation 6 hours ahead, but also able to correctly predict the evolution of rain bands from 6 to 12 hours in advance.

Bias-Corrected Short-Range Ensemble Forecasts for Near-Surface Variables during the Summer Season of 2010 in Northern China

A running mean bias （RMB） correction ap- proach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the northern China region. To determine a proper training window length for calculating RMB, window lengths from 2 to 20 days were evaluated, and 16 days was taken as an optimal window length, since it receives most of the benefit from extending the window length. The raw and 16-day RMB corrected ensembles were then evaluated for their ensemble mean forecast skills. The results show that the raw ensemble has obvious bias in all near-surface variables. The RMB correction can remove the bias reasonably well, and generate an unbiased ensemble. The bias correction not only reduces the ensemble mean forecast error, but also results in a better spreaderror relationship. Moreover, two methods for computing calibrated probabilistic forecast （PF） were also evaluated through the 57 case dates： 1） using the relative frequency from the RMB-eorrected ensemble; 2） computing the forecasting probabilities based on a historical rank histogram. The first method outperforms the second one, as it can improve both the reliability and the resolution of the PFs, while the second method only has a small effect on the reliability, indicating the necessity and importance of removing the systematic errors from the ensemble.

Forecasting method of monthly wind power generation based on climate model and long short-term memory neural network

Predicting wind power gen eration over the medium and long term is helpful for dispatchi ng departme nts,as it aids in constructing generation plans and electricity market transactions.This study presents a monthly wind power gen eration forecast!ng method based on a climate model and long short-term memory(LSTM)n eural n etwork.A non linear mappi ng model is established between the meteorological elements and wind power monthly utilization hours.After considering the meteorological data(as predicted for the future)and new installed capacity planning,the monthly wind power gen eration forecast results are output.A case study shows the effectiveness of the prediction method.

A Study on Reconstruction of Surface Wind Speed in China Due to Various Climate Variabilities

Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.

Progress in Climate Prediction and Weather Forecast Operations in China

The current status of weather forecasting and climate prediction, and the main progress China has made in recent years, are summarized in this paper. The characteristics and requirements of modern weather forecast operations are described briefly, and the significance of Numerical Weather Prediction （NWP） for future development is emphasized. Tile objectives and critical tasks for seamless short-term climate predic- tion that covers the extended-range （15 30 days）, monthly, seasonal, annual, interannual and interdecadal timescales, are proposed.

Study of Holocene glacier degradation in central Asia by isotopic methods for long-term forecast of climate changes

This article presents a summary of our studies of Holocene moraines and glaciers of the Tien-Shan, Pamir, and Himalaya moun- mills with the purpose of providing pattern regularity of the Holocene glaciation decomposition. We developed a method for ob- taining reliable radiocarbon dating of moraines with the use of autochthonous organic matter dispersed in fine-grained morainic material, as well there were shown new possibilities of isotope-oxygen and isotope-uranium analysis for the Holocene glaciations dynamics. We found that Holocene glaciations disintegrate stadiaUy according to the decaying principle, and seven main stages may be distinguished. We achieved the absolute dating of the first three stages, identifying these periods as 8,000, 5,000, and 3,400 years ago. The application of the above-mentioned isotope methods of the Holocene glaciations and moraines study will allow re- searchers to improve the offered model of the Holocene glaciations disintegration; it will be great contribution to salvation of the problem of long-term climatic and glaciations forecast.

The Obtaining and Verification of Meticulous Climate Forecast Product

[Objective] The aim was to study the obtaining method of meticulous climate forecast product and test its forecast effect. [Method] Based on the national standard surface observation data and secondary data bank obtained by means of distance weight interpolation method, the model of climate forecast was established, and the timing, fixed-point and quantitative meticulous climate forecast of meteorological elements was obtained by using many forecast methods and artificial revision, finally the forecast effect was tested. [Result] At present, meticulous climate forecast system was used to predict the daily, five-day, ten-day, monthly, seasonal and annual variation of six meteorological elements (including average temperature, maximum temperature, minimum temperature, precipitation, average pressure and sunshine) in 10 meteorological stations in Guangzhou City. The forecast effect of meteorological elements in 10 stations in Guangzhou City from 2006 to 2010 was tested, and the average scores of monthly precipitation, average temperature, maximum temperature and minimum temperature were 75.0, 94.5, 98.6 and 88.9, respectively, while the scores of five-day meteorological elements were 77.1, 90.6, 90.1 and 82.8, which met the requirement of objective management of Guangdong Meteorological Observatory. [Conclusion] Meticulous climate forecast system could be widely used in the forecast of agricultural meteorological disasters and fixed-point forecast in large reservoir, new airport and nuclear power station.

Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble Precipitation Forecasts over Iran

Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly forecasts for lead times of up to three months for public use.This study evaluated the ensemble forecasts of three C3S models over the period 1993-2017 in Iran’s eight classified precipitation clusters for one-to three-month lead times.Probabilistic and non-probabilistic criteria were used for evaluation.Furthermore,the skill of selected models was analyzed in dry and wet periods in different precipitation clusters.The results indicated that the models performed best in western precipitation clusters,while in the northern humid cluster the models had negative skill scores.All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons.Moreover,with increasing lead time,the forecast skill of the models worsened.In terms of forecasting in dry and wet years,the forecasts of the models were generally close to observations,albeit they underestimated several severe dry periods and overestimated a few wet periods.Moreover,the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models.In general,the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran.For the clusters considered in Iran and for the long-range system versions considered,the Météo France model had lower skill than the other models.

Comparison of different land-surface perturbation methods in short-range ensemble forecasts

In order to compare the sensitivity of short-range ensemble forecasts to different land-surface parameters in the South China region,three perturbation experiments related to the land surface model(LSM),initial soil moisture(ISM),and land–atmosphere coupling coefficient(LCC)were designed,and another control experiment driven by the Global Ensemble Forecast System(GEFS)was also performed.All ensemble members were initiated at 0000 UTC each day,and integrated for 24 h for a total of 40 days from the period 1 April to 10 May 2019 based on the Weather Research and Forecasting model.The results showed that the perturbation experiment of the LSM(LSMPE)had the largest ensemble spread,as well as the lowest ensemble-mean root-mean-square error among the three sets of land-surface perturbed experiments,which indicated that it could represent more uncertainty and less error.The ensemble spread of the perturbation experiment of the ISM(ISMPE)was generally less than that of LSMPE but greater than that of LCCPE(the perturbation experiment of the LCC).In particular,although the perturbation of the LCC could not produce greater spread,it had an effective influence on the intensity of precipitation.However,the ensemble spread of all the land-surface perturbed experiments was smaller than that of GEFSPE(the control experiment).Therefore,in future,land-surface perturbations and atmospheric perturbations should be combined in the design of ensemble forecasting systems to make the model represent more uncertainties.

Focus on Climate Impact Assessment and Forecast Service in Liaocheng City in 2015

Detailed statistics of characteristics of climatic factors in Liaocheng in 2015 were carried out. The main points of meteorological service＇ were summed up to im- prove the ability of meteorological forecast, thereby meeting the new requirements of the public for meteorological cause. The results showed that the annual average temperature in various Counties was in the range of 13.6-14.5 ℃, which was slight- ly higher than that in an average year and lower than that in the past year; the average annual precipitation of various counties ranged from 376.9 to 592.1 mm, which was slightly less than those in an average year and the past year; the aver- age sunshine duration across the city was 2 026 h, which was less than that in an average year and slightly more than that in the past year. The main climatic events included fog and haze, heavy snowfall, thunderstorm, gale, hail, high temperature, heavy rain and rainy sparse sunlight, which produced a negative impact on the agri- culture, tourism, transportation and people＇s daily life. This is the focus of future services.

The Potential of Hydro-Climate Forecast Strategies in Sustaining Agricultural Productivity amongst Rainfed Farmers in West Africa: A Review

Several studies have reported a significant yearly decrease in forest cover globally, using satellite images. This is especially true in West Africa, where rapid urbanisation acerbates the problem, and both of these changes lead to alterations in rainfall regime and other changes in climatic parameters. Several studies reveal that adaptation which reduces vulnerability to adverse climatic variation effects is the key to developing resilience against climate change. In this region, over 90% of farmers are engaged in small-scale rainfed crop cultivation and rely on their own weather perception, instincts and what they observe from the surrounding biota (flora and fauna) to forecast the weather and plan their agricultural activities. The pressing nature of the problem of climate variability in Africa had provoked a lot of research into developing and testing several adaptation strategies to control the situation. Various strategies to improve and localize global, regional and national climate services (Local Forecast, Scientific Forecast and Integrated Forecast) needed by the farmers are being developed to build resilience against climate change. This review illustrates the situation in Ghana and identifies various forecast strategies developed to mitigate the adverse effects of climate variability on agricultural productivity. These mitigation methods include the development of climate services to provide users with forecast information in order to make climate-smart decisions to minimize the risk.

STUDY OF THE EFFECTS OF REDUCING SYSTEMATIC ERRORS ON MONTHLY REGIONAL CLIMATE DYNAMICAL FORECAST

A nested-model system is constructed by embedding the regional climate model RegCM3 into a general circulation model for monthly-scale regional climate forecast over East China. The systematic errors are formulated for the region on the basis of 10-yr (1991-2000) results of the nested-model system, and of the datasets of the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the temperature analysis of the National Meteorological Center (NMC), U.S.A., which are then used for correcting the original forecast by the system for the period 2001-2005. After the assessment of the original and corrected forecasts for monthly precipitation and surface air temperature, it is found that the corrected forecast is apparently better than the original, suggesting that the approach can be applied for improving monthly-scale regional climate dynamical forecast.