Weather Yield Model for the Semi Tropical Region (Pakistan)

Weather models are essential tools for checking of the effect of the weather elements in terms of their effect on the production of the crop. This research is an attempt to see the effect of only two variables i.e., temperature and rainfall for the division Faisalabad (semitropical region of Pakistan).The model fitted is of the linear form:the values of a,b, c have been found. The expected yield has been calculated by using the aridity indices (X1 and X2 ) and the result in the form of coefficient of determination R2 has been found equal to 0.166. The significance of the regression coefficient has been tested, which shows that the contribution to the yield from aridity index at germination and that at ripening is significant.The wheat yields are the results of a wide variety of variables, most of which show varying degree of relationship with one another, some positive and some negative in terms of output. These variables may be technology, fertilizers, pesticides, epidemics, kinds of seeds used, market price of crop and the area under cultivation etc, which can be the source of variation in the wheat yield. Since rainfall during germination and temperature at the ripening periods are the necessary factors for the yield of wheat, for this purpose these parameters have been studied in order to their contribution.

Collating Historic Weather Observations for the East Asian Region： Challenges, Solutions, and Reanalyses

1. IntroductionHistoric instrumental weather observations, made on land or at sea from as early as the 17th century （e.g.,Camuffo et al.,2010）,are integral to extending our understanding of the decadal and centennial variations of Earth＇s climate and for comparison with paleo-proxy data.

Use of Microwave Radiances from Metop-C and Fengyun-3 C/D Satellites for a Northern European Limited-area Data Assimilation System

MetCoOp is a Nordic collaboration on operational Numerical Weather Prediction based on a common limited-area km-scale ensemble system. The initial states are produced using a 3-dimensional variational data assimilation scheme utilizing a large amount of observations from conventional in-situ measurements, weather radars, global navigation satellite system, advanced scatterometer data and satellite radiances from various satellite platforms. A version of the forecasting system which is aimed for future operations has been prepared for an enhanced assimilation of microwave radiances. This enhanced data assimilation system will use radiances from the Microwave Humidity Sounder, the Advanced Microwave Sounding Unit-A and the Micro-Wave Humidity Sounder-2 instruments on-board the Metop-C and Fengyun-3 C/D polar orbiting satellites. The implementation process includes channel selection, set-up of an adaptive bias correction procedure, and careful monitoring of data usage and quality control of observations. The benefit of the additional microwave observations in terms of data coverage and impact on analyses, as derived using the degree of freedom of signal approach, is demonstrated. A positive impact on forecast quality is shown, and the effect on the precipitation for a case study is examined. Finally, the role of enhanced data assimilation techniques and adaptions towards nowcasting are discussed.

Diagnostic Quantification of the Cloud Water Resource in China during 2000–2019

By using the diagnostic quantification method for cloud water resource(CWR),the three-dimensional(3D)cloud fields of 1°×1°resolution during 2000-2019 in China are firstly obtained based on the NCEP reanalysis data and related satellite data.Then,combined with the Global Precipitation Climatology Project(GPCP)products,a 1°×1°gridded CWR dataset of China in recent 20 years is established.On this basis,the monthly and annual CWR and related variables in China and its six weather modification operation sub-regions are obtained,and the CWR characteristics in different regions are analyzed finally.The results show that in the past 20 years,the annual total amount of atmospheric hydrometeors(GM_(h))and water vapor(GM_(v))in the Chinese mainland are about 838.1 and 3835.9 mm,respectively.After deducting the annual mean precipitation of China(P_(s),661.7 mm),the annual CWR is about 176.4 mm.Among the six sub-regions,the southeast region has the largest amount of cloud condensation(C_(vh))and precipitation,leading to the largest GM_(h) and CWR there.In contrast,the annual P_(s),GM_(h),and CWR are all the least in the northwest region.Furthermore,the monthly and interannual variation trends of P_(s),C_(vh),and GM_(h) in different regions are identical,and the evolution characteristics of CWR are also consistent with the hydrometeor inflow(Q_(hi)).For the north,northwest,and northeast regions,in spring and autumn the precipitation efficiency of hydrometeors(PEh)is not high(20%-60%),the renewal time of hydrometeors(RT_(h))is relatively long(5-25 h),and GM_(h) is relatively high.Therefore,there is great potential for the development of CWR through artificial precipitation enhancement(APE).For the central region,spring,autumn,and winter are suitable seasons for CWR development.For the southeast and southwest regions,P_(s) and PE_(h) in summer are so high that the development of CWR should be avoided.For different spatial scales,there are significant differences in the characteristics of CWR.