Oceanic Indices for Forecasting Seasonal Rainfall over the Northern Part of Brazilian Northeast

A relationship between oceanic conditions in the northwestern equatorial Atlantic (NWEA) and the seasonal rainfall over the northern part of Brazilian Northeast (NNEB) allows large climate events to be forecasted with a delay of a few months. Observed sea surface variables (sea surface temperature, wind stress and latent heat flux) and reanalyzed temperature and salinity profiles at depths of 0 - 150 m are used during 1974-2008. Perturbations in the Wind-Evaporation-SST mechanism over the NWEA during the last months of the year and the first months of the following year are of primary importance in evaluating the risk that strong climate events will affect the subsequent seasonal rainfall (in March-April) over the NNEB. Especially interesting are the Barrier Layer Thickness (BLT) and Ocean Heat Content (OHC) in the NWEA region from August-September through the subsequent months, during which a slow and steady evolution is apparent, with the highest signal occurring in October-November. Through their relationship with the local surface dynamic conditions, such BLT and OHC perturbations during the last months of the year can be used as a valuable indicator for forecasting wet or dry events over the NNEB during the subsequent rainfall season. A proposal is discussed to deploy additional temperature/conductivity sensors down to a depth of 140 m at three PIRATA moorings located in the NWEA region. That will be necessary if the BLT and other parameters of energy exchange between the ocean and atmosphere are to be estimated in real time and with a sufficiently high vertical resolution.

Seasonal Rainfall Forecasts for the Yangtze River Basin of China in Summer 2019 from an Improved Climate Service

Rainfall forecasts for the summer monsoon season in the Yangtze River basin(YRB) allow decision-makers to plan for possible flooding, which can affect the lives and livelihoods of millions of people. A trial climate service was developed in 2016, producing a prototype seasonal forecast product for use by stakeholders in the region, based on rainfall forecasts directly from a dynamical model. Here, we describe an improved service based on a simple statistical downscaling approach. Through using dynamical forecast of an East Asian summer monsoon(EASM) index, seasonal mean rainfall for the upper and middle/lower reaches of YRB can be forecast separately by use of the statistical downscaling, with significant skills for lead times of up to at least three months. The skill in different sub-basin regions of YRB varies with the target season. The rainfall forecast skill in the middle/lower reaches of YRB is significant in May–June–July(MJJ), and the forecast skill for rainfall in the upper reaches of YRB is significant in June–July–August(JJA). The mean rainfall for the basin as a whole can be skillfully forecast in both MJJ and JJA. The forecasts issued in 2019 gave good guidance for the enhanced rainfall in the MJJ period and the near-average conditions in JJA. Initial feedback from users in the basin suggests that the improved forecasts better meet their needs and will enable more robust decision-making.

Relationships between Rainy Days,Mean Daily Intensity and Seasonal Rainfall in Normal,Flood and Drought Years over India

here are limitations in using the seasonal rainfall total in studies of Monsoon rainfall climatology. A correlation analysis of the individual station seasonal rainfall with all India seasonal mean rainfall has been made. After taking the significance test (strictly up to 5% level) the stations which are significantly correlated have been considered in this study in normal, flood and drought years respectively. Analysis of seasonal rainfall data of 50 stations spread over a period of 41 years suggests that a linear relationship fits better than the logarithmic relationship when seasonal rainfall versus number of rainy days is studied. The linear relationship is also found to be better in the case of seasonal rainfall versus mean daily intensity.

Two Opposite Extreme Events in Seasonal Mean Winter Rainfall over East China during the Past Three Decades

In this study,the extremes of winter seasonal mean precipitation have been investigated by using daily precipitation data from 91 stations in East China,the National Centers for Environmental Prediction/the National Center for Atmospheric Research （NCEP/NCAR） monthly reanalysis,and sea surface temperature data from the Hadley Centre for 1979-2007.The largest anomalous rainfall amount was observed in regions south of the Yangtze River.In the most recent three decades,extreme events in the seasonal mean winter precipitation occurred in 1985 and 1997.Because it was influenced mainly by a La Ni（n）a event,the precipitation in 1985 showed a deficit following a stronger winter monsoon.The rainfall amount in 1997 was influenced by E1 Ni（n）o and was significantly larger than normal with a weaker winter monsoon.Both the circulation anomalies and wave energy dispersions during the winters of 1985 and 1997 differed significantly.In 1985,the North Atlantic Oscillation anomalously excited the Eurasian-Pacific teleconnection and circumglobal teleconnection phenomena.Consequently,Rossby wave energy propagated along the north and south branches of the westerlies,strengthening the East Asian trough along with a stronger winter monsoon,which facilitated the wintertime dry extreme in East China.In 1997,however,Rossby wave energy propagated from low latitudes northeastward into the southern part of China,resulting in a weaker winter monsoon and the wettest winter.The results of this study will be helpful for future monitoring and prediction of extreme winter rainfall events in East China.

Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia

Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment.Although there are enough historical evidence to support the theory that climate change is a natural phenomenon,many research scientists are widely in agreement that the increase in temperature in the 20 th century is anthropologically related.The associated effects are the variability of rainfall and cyclonic patterns that are being observed globally.In Southeast Asia the link between global warming and the seasonal atmospheric flow during the monsoon seasons shows varying degree of fuzziness.This study investigates the impact of climate change on the seasonality of monsoon Asia and its effect on the variability of monsoon rainfall in Southeast Asia.The comparison of decadal variation of precipitation and temperature anomalies before the 1970 s found general increases which were mostly varying.But beyond the 1970 s,global precipitation anomalous showed increases that almost corresponded with increases in global temperature anomalies for the same period.There are frequent changes and a shift westward of the Indian summer monsoon.Although precipitation is observed to be 70%below normal levels,in some areas the topography affects the intensity of rainfall.These shifting phenomenon of other monsoon season in the region are impacting on the variability of rainfall and the onset of monsoons in Southeast Asia and is predicted to delay for 15 days the onset of the monsoon in the future.The variability of monsoon rainfall in the SEA region is observed to be decadal and the frequency and intensity of intermittent flooding of some areas during the monsoon season have serious consequences on the human,financial,infrastructure and food security of the region.

The Impacts of Topography on Spatial and Temporal Rainfall Distribution over Rwanda Based on WRF Model

The impact of topography on heavy rainfall during two rain seasons was investigated in order to explain their mechanisms on rainfall distribution over Rwanda. Weather Research and Forecasting (WRF-ARW) model was used to study two historical cases of heavy rainfall which took place over Rwanda during two rain seasons, March to May (MAM) and September to December (SOND), from April 7 to 9, 2012 (for MAM) and from October 29 to 31, 2012 (during SOND). The control experiment was done with actual topography, whereas sensitivity experiment was carried out with topography reduced by half. Results show that rainfall distribution over Rwanda significantly changes when topography is reduced. The reduction in topography leads to a decrease in rainfall amounts in both MAM and SOND seasons, with varying magnitudes. This reveals the importance of orography in determining rainfall amounts and distribution over the region. The accumulated rainfall amount from WRF underestimate or overestimate rain gauge stations data by region and by season, but there is good agreement especially in altitude below 1490 m and above 1554 m during April and October respectively. The results may motivate modelling carters to further improve parameterization schemes in the mountainous regions.

Spatial Characteristics of Extreme Rainfall over China with Hourly through 24-Hour Accumulation Periods Based on National-Level Hourly Rain Gauge Data

Hourly rainfall measurements of 1919 national-level meteorological stations from 1981 through 2012 are used to document,for the first time,the climatology of extreme rainfall in hourly through 24-h accumulation periods in China. Rainfall amounts for 3-,6-,12- and 24-h periods at each station are constructed through running accumulation from hourly rainfall data that have been screened by proper quality control procedures. For each station and for each accumulation period,the historical maximum is found,and the corresponding 50-year return values are estimated using generalized extreme value theory. Based on the percentiles of the two types of extreme rainfall values among all the stations,standard thresholds separating Grade I,Grade II and Grade III extreme rainfall are established,which roughly correspond to the 70th and 90th percentiles for each of the accumulation periods. The spatial characteristics of the two types of extreme rainfall are then examined for different accumulation periods. The spatial distributions of extreme rainfall in hourly through 6-h periods are more similar than those of 12- and 24-h periods. Grade III rainfall is mostly found over South China,the western Sichuan Basin,along the southern and eastern coastlines,and in the large river basins and plains. There are similar numbers of stations with Grade III extreme hourly rainfall north and south of 30°N,but the percentage increases to about 70% south of 30°N as the accumulation period increases to 24 hours,reflecting richer moisture and more prolonged rain events in southern China. Potential applications of the extreme rainfall climatology and classification standards are suggested at the end.

THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON

An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season(AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall;the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.

THE IMPACT OF PRECEDING ATMOSPHERIC CIRCULATION AND SST VARIATION ON FLOOD SEASON RAINFALL IN YUNNAN

Spatial and temporal distribution characteristics and scale range of two significant areas were obtained by analyzing the relationship among summer rainfall in Yunnan province, height field and SST field (40°S – 40°N, 30 °E – 70°W) across the North Hemisphere at 200 hPa, 500 hPa and 850 hPa for Jan. to May and correlation, and field wave structure. Remote key regions among summer rainfall in Yunnan province, height field and SST field (40°S – 40°N, 30°E – 70°W) across the North Hemisphere at 200 hPa, 500 hPa and 850 hPa were studied through further analyzing of the circulation system and its climate / weather significance. The result shows that the forecast has dependable physical basis when height and SST fields were viewed as predictors and physical models of impacts on rainy season precipitation in Yunnan are preliminarily concluded.

Estimating rainfall erosivity by incorporating seasonal variations in parameters into the Richardson model

Rainfall erosivity is an important climatic factor for predicting soil loss. Through the application of high-resolution pluviograph data at 5 stations in Huangshan City, Anhui Prov- ince, China, we analyzed the performance of a modified Richardson model that incorporated the seasonal variations in parameters α andβ. The results showed that （1） moderate to high seasonality was presented in the distribution of erosive rainfall, and the seasonality of rainfall erosivity was even stronger; （2） seasonal variations were demonstrated in both parameters α and β of the Richardson model; and （3） incorporating and coordinating the seasonality of parameters αandβgreatly improved the predictions at the monthly scale. This newly modi- fied model is therefore highly recommended when monthly rainfall erosivity is required, such as, in planning soil and water conservation practices and calculating the cover-management factor in the Universal Soil Loss Equation （USLE） and Revised Universal Soil Loss Equation （RUSLE）.

Asian monsoon shaped the pattern of woody dicotyledon richness in humid regions of China

Understanding how geographical patterns of plant richness are established is a key scientific question in ecology and biogeography.Climate factors,such as environmental energy,water availability,and rainfall seasonality,have been widely proposed to account for geographical patterns of plant richness at large scales.Using a compiled distribution data set of 3166 native woody dicotyledons across 732 calibration grids at the county level in humid regions of China,we explored the geographical pattern of woody dicotyledon richness and its relationship to climatic variations,especially the Asian monsoonal climate.We found that species richness decreases with increasing latitude.Our study indicates that water availability(particularly mean annual precipitation,MAP)is the major abiotic factor in determining large-scale distribution patterns of species richness,Moreover,the seasonality of rainfall variables under the Asian monsoon climate largely contributes to species richness,because species richness correlates more significantly with precipitation during the three driest consecutive months(P3 DRY)than precipitation during the three wettest consecutive months(P3 WET).Therefore,we conclude that woody dicotyledon richness in humid regions of China is mainly affected by the Asian winter monsoon.

Assessment of the Impacts of Tropical Cyclone Fantala to Tanzania Coastal Line: Case Study of Zanzibar

The study investigated the impacts of tropical cyclone (TC) Fantala (11th to 27th April, 2016) to the coastal areas of Tanzania, Zanzibar in particular. Daily reanalysis data consisting of wind speed, sea level pressure (SLP), sea surface temperatures (SSTs) anomaly, and relative humidity from the National Centres for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) were used to analyze the variation in strength of Fantala as it was approaching the Tanzania coastal line. In addition observed rainfall from Tanzania Meteorological Authority (TMA) at Zanzibar office, Global Forecasting System (GFS) rainfall estimates and satellite images were used to visualize the impacts of tropical cyclone Fantala to Zanzibar. The results revealed that, TC Fantala was associated with deepening/decreasing in SLP (from 1012 - 1010 mb) around the north-western Madagascar and coastal Tanzania, whereas the mean SSTs was greater than 28°C and an SSTs anomaly ranged from 0 to 2.3°C. The vertical wind shear which ridged at Mozambican Channel and over north-eastern Madagascar was high enough (12 - 15 ms-1) to support the intensifying of Fantala. The thermodynamic and dynamic conditions of Fantala influenced heavy rainfall of greater than 170 mm over most stations in Zanzibar. Moreover, Fantala disrupted the temporal variability of 2016 March to May (MAM) seasonal rainfall. Besides, more than 420 people were homeless, at least 3330 houses were destroyed, and about 2 people died. As for mainland Tanzania Fantala resulted in a death of 12 people in Kilimanjaro and Arusha, more than 315 houses were washed away by flooding leading to 13,933 people being homeless. Conclusively the study calls for an extensive research work based on examining and forecasting the TCs rainfall impacts and their contribution during the two rainfall seasons of OND and MAM in Tanzania.

Dynamical and Machine Learning Hybrid Seasonal Prediction of Summer Rainfall in China

Seasonal prediction of summer rainfall is crucial to reduction of regional disasters,but currently it has a low prediction skill.We developed a dynamical and machine learning hybrid(MLD)seasonal prediction method for summer rainfall in China based on circulation fields from the Chinese Academy of Sciences(CAS)Flexible Global Ocean-Atmosphere-Land System Model finite volume version 2(FGOALS-f2)operational dynamical prediction model.Through selecting optimum hyperparameters for three machine learning methods to obtain the best fit and least overfitting,an ensemble mean of the random forest and gradient boosting regression tree methods was shown to have the highest prediction skill measured by the anomalous correlation coefficient.The skill has an average value of 0.34 in the historical cross-validation period(1981-2010)and 0.20 in the 10-yr period(2011-2020)of independent prediction,which significantly improves the dynamical prediction skill by 400%.Both reducing overfitting and using the best dynamical prediction are important in applications of the MLD method and in-depth analysis of these warrants a further investigation.

The Influence of Climate Variability on the Watermelon Production in Zanzibar

Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Currently, there is either no or scant information that describes the influence of climate changes and variability to watermelon production in Zanzibar. Thus, this study aimed to determine the influence of climate variability on the quantity of watermelon production in Zanzibar. The study used both primary and secondary datasets, which include the anecdotal information collected from interviewers’ responses from four districts of Unguja and Pemba, and climate parameters (rainfall, maximum and minimum temperature (Tmax and Tmin) acquired from Tanzania Meteorological Authority (TMA) at Zanzibar offices. Pearson correlation was used for analyzing the association between watermelon production and climate parameters, while paired t-test was applied to show the significance of the mean differences of watermelon and climate parameters for two periods of 2014-2017 and 2018-2021, respectively. Percentage changes were used to feature the extent to which the two investigated parameters affect each other. The anecdotal responses were sorted, calculated in monthly and seasonal averages, plotted and then analyzed. Results have shown a strong correlation (r = 0.8 at p ≤ 0.02, and r = 0.7) between watermelon production, Tmax and rainfall during OND, especially in Unguja, as well as Tmin during JJA (i.e. r = - 0.8 at p ≤ 0.02) in Pemba. Besides, results have shown the existence of significant differences between the means of watermelon production and climate parameter for the two stated periods, indicating that the climate parameters highly affects the watermelon production by either enhancing or declining the yields by 69% - 162% and 17% - 77%, respectively. Moreover, results have shown that respondents were aware that excess temperature intensity during dry periods can lead to high production costs due number of soil and other environmental factors. Besides the results have shown that OND seasonal rainfall and MAM Tmax had good association with watermelon production in Unguja while JJA Tmin declined the production in Pemba. Thus, the study concludes that seasonal variability of climate parameter has a significant influence on the watermelon production. The study calls for more studies on factors affecting watermelon production (e.g. soil characteristics, pest sides and manure), and recommends for climate based decision making on rain fed agricultural yields and routine monitoring of weather information.

Duration and Seasonality of Hourly Extreme Rainfall in the Central Eastern China

Compared with daily rainfall amount, hourly rainfall rate represents rainfall intensity and the rainfall process more accurately, and thus is more suitable for studies of extreme rainfall events. The distribution functions of annual maximum hourly rainfall amount at 321 stations in China are quantified by the Generalized Extreme Value（GEV） distribution, and the threshold values of hourly rainfall intensity for 5-yr return period are estimated. The spatial distributions of the threshold exhibit significant regional diferences, with low values in northwestern China and high values in northern China, the mid and lower reaches of the Yangtze River valley, the coastal areas of southern China, and the Sichuan basin. The duration and seasonality of the extreme precipitation with 5-yr return periods are further analyzed. The average duration of extreme precipitation events exceeds 12 h in the coastal regions, Yangtze River valley, and eastern slope of the Tibetan Plateau. The duration in northern China is relatively short. The extreme precipitation events develop more rapidly in mountain regions with large elevation diferences than those in the plain areas. There are records of extreme precipitation in as early as April in southern China while extreme rainfall in northern China will not occur until late June. At most stations in China, the latest extreme precipitation happens in August–September. The extreme rainfall later than October can be found only at a small portion of stations in the coastal regions, the southern end of the Asian continent, and the southern part of southwestern China.

STUDY ON THE RELATIONSHIP BETWEEN THE DECADAL VARIATIONS OF ANNUALLY FIRST RAINY SEASON PRECIPITATION OF GUANGXI AND SEA SURFACE TEMPERATURE OF INDIAN OCEAN IN SOUTHERN HEMISPHERE

Decadal circulation differences between more and less rainfall periods in the annually first rainy season of Guangxi and their association with sea surface temperature (SST) of the austral Indian Ocean are investigated by using the NCEP/NCAR reanalysis data. The results are shown as follows. A pattern in which there is uniform change of the Guangxi precipitation shows a 20-year decadal oscillation and a 3-year interannual change. In contrast, a pattern of reversed-phase change between the north and the south of Guangxi has a 6-year interannual periodicity and quasi-biennial oscillation. In the period of more precipitation, the surface temperature in Eurasia is positively anomalous so as to lead to stronger low pressure systems on land and larger thermal contrast between land and ocean. Therefore, the air column is more unstable and ascending flows over Guangxi are intensified while the Hadley cell is weakened. Furthermore, the weaker western Pacific subtropical high and South Asia High, together with a stronger cross-equatorial flow, result in the transportation of more humidity and the appearance of more precipitation. The correlation analysis indicates that the Indian Ocean SST in Southern Hemisphere is closely associated with the variation of the seasonal precipitation of Guangxi on the decadal scale by influencing the Asian monsoon through the cross-equatorial flow.

Assimilating Doppler radar observations with an ensemble Kalman filter for convection-permitting prediction of convective development in a heavy rainfall event during the pre-summer rainy season of South China

This study examines the effectiveness of an ensemble Kalman filter based on the weather research and forecasting model to assimilate Doppler-radar radial-velocity observations for convection-permitting prediction of convection evolution in a high-impact heavy-rainfall event over coastal areas of South China during the pre-summer rainy season. An ensemble of 40 deterministic forecast experiments(40 DADF) with data assimilation(DA) is conducted, in which the DA starts at the same time but lasts for different time spans(up to 2 h) and with different time intervals of 6, 12, 24, and 30 min. The reference experiment is conducted without DA(NODA).To show more clearly the impact of radar DA on mesoscale convective system(MCS)forecasts, two sets of 60-member ensemble experiments(NODA EF and exp37 EF) are performed using the same 60-member perturbed-ensemble initial fields but with the radar DA being conducted every 6 min in the exp37 EF experiments from 0200 to0400 BST. It is found that the DA experiments generally improve the convection prediction. The 40 DADF experiments can forecast a heavy-rain-producing MCS over land and an MCS over the ocean with high probability, despite slight displacement errors. The exp37 EF improves the probability forecast of inland and offshore MCSs more than does NODA EF. Compared with the experiments using the longer DA time intervals, assimilating the radial-velocity observations at 6-min intervals tends to produce better forecasts. The experiment with the longest DA time span and shortest time interval shows the best performance.However, a shorter DA time interval(e.g., 12 min) or a longer DA time span does not always help. The experiment with the shortest DA time interval and maximum DA window shows the best performance, as it corrects errors in the simulated convection evolution over both the inland and offshore areas. An improved representation of the initial state leads to dynamic and thermodynamic conditions that are more conducive to earlier initiation of the inland MCS and longer maintenance of the offshore MCS.

Using Moving North Pacific Index to Improve Rainy Season Rainfall Forecast over the Yangtze River Basin by Analog Error Correction

A new analog error correction （AEC） scheme based on the moving North Pacific index （MNPI） is designed in this study. This scheme shows obvious improvement in the prediction skill of the operational coupled general circulation model （CGCM） of the National Climate Center of China for the rainy season rainfall （RSR） anomaly pattern correlation coefficient （ACC） over the mid-to-lower reaches of the Yangtze River （MLRYR）. A comparative analysis indicates that the effectiveness of the new scheme using the MNPI is better than the system error correction scheme using the North Pacific index （NPI）. A Euclidean distance- weighted mean rather than a traditional arithmetic mean, is applied to the integration of the analog year＇s prediction error fields. By using the MNPI AEC scheme, independent sample hindcasts of RSR during the period 2003-2009 are then evaluated. The results show that the new scheme exhibited a higher forecast skill during 2003-2009, with an average ACC of 0.47; while the ACC for the NPI case was only 0.19. Furthermore, the forecast skill of the RSR over the MLRYR is examined. In the MNPI case, empirical orthogonal function （EOF） was used in the degree compression of the prediction error fields from the CCCM, whereas the AEC scheme was applied only to its first several EOF components for which the accumulative explained variance accounted for 80% of the total variance. This further improved the ACC of the independent sample hindcasts to 0.55 during the 7-yr period.

Quantifying extreme climatic conditions for maize production using RZWQM in Siping,Northeast China

Climate change has a great influence on agricultural production,especially under extreme climatic conditions.In this study,Root Zone Water Quality Model(RZWQM)was used to predict grain yields of maize in the Siping region,Jilin Province,Northeast China during the period from 1951 to 2015;and the response of grain yield to main climatic variables was qualitatively analyzed,especially in three special years of 1954,2000 and 2009.Results showed that 1℃ increase for minimum,maximum and mean air temperatures may produce 1224 kg/hm^(2),1860 kg/hm^(2) and 1540 kg/hm^(2) more grain yields,respectively,and seasonal rainfall amount of less than 450 mm,especially at the flowering and grain filling stages,greatly reduced grain yields.In the years of 1954,2000 and 2009,grain yields were reduced by 41%,47%and 40%compared to their mean value,respectively,correspondingly because of extra low temperature(lower by 2.1℃-2.3℃),less rainfall at the grain filling stage(36 mm)and extra high temperature(higher by 1.7℃-1.8℃),and less seasonal rainfall(252 mm).To reduce extreme climate’s effects on grain yield,it is suggested that supplementary irrigation at the flowering and grain filling stages should be provided when rainfall is much less at this stage and also appropriate maize species based on the longtime weather forecast should be selected.