Understanding the characteristics of cloud water resource(CWR)and precipitation efficiency of hydrometeors(PEh)is imperative for the application of CWR in Northwest China.The atmospheric precipitable water(PW)in all f...Understanding the characteristics of cloud water resource(CWR)and precipitation efficiency of hydrometeors(PEh)is imperative for the application of CWR in Northwest China.The atmospheric precipitable water(PW)in all four seasons and clouds and PEh in summer were studied with ERA-5 and CloudSat data in this region.The results show that topography,especially in the Tibetan Plateau,exerts significant impacts on the precipitation and PW in summer,since large amounts of clouds are distributed along the mountain ranges.The study region is divided into four typical areas:the monsoon area in eastern Northwest China(NWE),the Qilian Mountains area(QM),the Tianshan Mountains area(TM),and the Source of Three Rivers area(STR).Over the four areas,cloud top height(6.3 km)and cloud base height(3.3 km)over NWE are higher,and precipitating clouds are thicker(7 km)in the single-layer clouds.Liquid water content decreases with increasing altitude,while the ice water content first increases and then decreases.Liquid water path is higher over NWE(0.11 kg m^(−2))than over TM and STR(0.05 kg m^(−2)),and the ice water path is mainly concentrated within the range of 0.025–0.055 kg m^(−2).The PEh values are distributed unevenly and affected evidently by the terrain.Although the PEh values in the four typical areas(0.3–0.6)are higher than those in other regions,the CWR is relatively abundant and has a higher exploitation potential.Therefore,it is well-founded to exploit CWR for alleviating water shortages in these areas of Northwest China in summer.展开更多
The water in the air is composed of water vapor and hydrometeors,which are inseparable in the global atmosphere.Precipitation basically comes from hydrometeors instead of directly from water vapor,but hydrometeors are...The water in the air is composed of water vapor and hydrometeors,which are inseparable in the global atmosphere.Precipitation basically comes from hydrometeors instead of directly from water vapor,but hydrometeors are rarely focused on in previous studies.When assessing the maximum potential precipitation,it is necessary to quantify the total amount of hydrometeors present in the air within an area for a certain period of time.Those hydrometeors that have not participated in precipitation formation in the surface,suspending in the atmosphere to be exploited,are defined as the cloud water resource(CWR).Based on the water budget equations,we defined 16 terms(including 12 independent ones)respectively related to the hydrometeors,water vapor,and total water substance in the atmosphere,and 12 characteristic variables related to precipitation and CWR such as precipitation efficiency(PE)and renewal time(RT).Correspondingly,the CWR contributors are grouped into state terms,advection terms,and source/sink terms.Two methods are developed to quantify the CWR(details of which are presented in the companion paper)with satellite observations,atmospheric reanalysis data,precipitation products,and cloud resolving models.The CWR and related variables over North China in April and August 2017 are thus derived.The results show that CWR has the same order of magnitude as surface precipitation(Ps).The hydrometers converted from water vapor(Cvh)during the condensation process is the primary source of precipitation.It is highly correlated with Ps and contributes the most to the CWR over a large region.The state variables and advection terms of hydrometeors are two orders of magnitude lower than the corresponding terms of water vapor.The atmospheric hydrometeors can lead to higher PE than water vapor(several tens of percent versus a few percent),with a shorter RT(only a few hours versus several days).For daily CWR,the state terms are important,but for monthly and longer-time mean CWR,the source/sink terms(i.e.,cloud microphysical processes)contribute the largest;meanwhile,the advection terms contribute less for larger study areas.展开更多
Based on the concepts of cloud water resource(CWR)and related variables proposed in the first part of this study,this paper provides details of two methods to quantify the CWR.One is diagnostic quantification(CWR-DQ)b...Based on the concepts of cloud water resource(CWR)and related variables proposed in the first part of this study,this paper provides details of two methods to quantify the CWR.One is diagnostic quantification(CWR-DQ)based on satellite observations,precipitation products,and atmospheric reanalysis data;and the other is numerical quantification(CWR-NQ)based on a cloud resolving model developed at the Chinese Academy of Meteorological Sciences(CAMS).The two methods are applied to quantify the CWR in April and August 2017 over North China,and the results are evaluated against all available observations.Main results are as follows.(1)For the CWR-DQ approach,reference cloud profiles are firstly derived based on the Cloud Sat/CALIPSO joint satellite observations for 2007–2010.The NCEP/NCAR reanalysis data in 2000–2017 are then employed to produce three-dimensional cloud fields.The budget/balance equations of atmospheric water substance are lastly used,together with precipitation observations,to retrieve CWR and related variables.It is found that the distribution and vertical structure of clouds obtained by the diagnostic method are consistent with observations.(2)For the CWR-NQ approach,it assumes that the cloud resolving model is able to describe the cloud microphysical processes completely and precisely,from which four-dimensional distributions of atmospheric water vapor,hydrometeors,and wind fields can be obtained.The data are then employed to quantify the CWR and related terms/quantities.After one-month continuous integration,the mass of atmospheric water substance becomes conserved,and the tempospatial distributions of water vapor,hydrometeors/cloud water,and precipitation are consistent with observations.(3)Diagnostic values of the difference in the transition between hydrometeors and water vapor(Cvh-Chv)and the surface evaporation(Es)are well consistent with their numerical values.(4)Correlation and bias analyses show that the diagnostic CWR contributors are well correlated with observations,and match their numerical counterparts as well,indicating that the CWR-NQ and CWR-DQ methods are reasonable.(5)Underestimation of water vapor converted from hydrometeors(Chv)is a shortcoming of the CWR-DQ method,which may be rectified by numerical quantification results or by use of advanced observations on higher spatiotemporal resolutions.展开更多
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 rean...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.展开更多
Based on the concept of cloud water resource(CWR)and the cloud microphysical scheme developed by the Chinese Academy of Meteorological Sciences(CAMS),a coupled mesoscale and cloud-resolving model system is developed i...Based on the concept of cloud water resource(CWR)and the cloud microphysical scheme developed by the Chinese Academy of Meteorological Sciences(CAMS),a coupled mesoscale and cloud-resolving model system is developed in the study for CWR numerical quantification(CWR-NQ)in North China for 2017.The results show that(1)the model system is stable and capable for performing 1-yr continuous simulation with a water budget error of less than 0.2%,which indicates a good water balance.(2)Compared with the observational data,it is confirmed that the simulating capability of the CWR-NQ approach is decent for the spatial distribution of yearly cumulative precipitation,daily precipitation intensity,yearly average spatial distribution of water vapor.(3)Compared with the CWR diagnostic quantification(CWR-DQ),the results from the CWR-NQ differ mainly in cloud condensation and cloud evaporation.However,the deviation of the net condensation(condensation minus evaporation)between the two methods is less than 1%.For other composition variables,such as water vapor advection,surface evaporation,precipitation,cloud condensation,and total atmospheric water substances,the relative differences between the CWR-NQ and the CWR-DQ are less than 5%.(4)The spatiotemporal features of the CWR in North China are also studied.The positive correlation between water vapor convergence and precipitation on monthly and seasonal scales,and the lag of precipitation relative to water vapor convergence on hourly and daily scales are analyzed in detail,indicating the significance of the state term on hourly and daily scales.The effects of different spatial scales on the state term,advection term,source-sink term,and total amount are analyzed.It is shown that the advective term varies greatly at different spatiotemporal scales,which leads to differences at different spatiotemporal scales in CWR and related characteristic quantities.展开更多
基金Supported by the National Natural Science Foundation of China(41775139)Ministry of Science and Technology of China(2016YFE0201900 and GYHY201406033)China Meteorological Administration(ZQC-R18169/RYSY201904).
文摘Understanding the characteristics of cloud water resource(CWR)and precipitation efficiency of hydrometeors(PEh)is imperative for the application of CWR in Northwest China.The atmospheric precipitable water(PW)in all four seasons and clouds and PEh in summer were studied with ERA-5 and CloudSat data in this region.The results show that topography,especially in the Tibetan Plateau,exerts significant impacts on the precipitation and PW in summer,since large amounts of clouds are distributed along the mountain ranges.The study region is divided into four typical areas:the monsoon area in eastern Northwest China(NWE),the Qilian Mountains area(QM),the Tianshan Mountains area(TM),and the Source of Three Rivers area(STR).Over the four areas,cloud top height(6.3 km)and cloud base height(3.3 km)over NWE are higher,and precipitating clouds are thicker(7 km)in the single-layer clouds.Liquid water content decreases with increasing altitude,while the ice water content first increases and then decreases.Liquid water path is higher over NWE(0.11 kg m^(−2))than over TM and STR(0.05 kg m^(−2)),and the ice water path is mainly concentrated within the range of 0.025–0.055 kg m^(−2).The PEh values are distributed unevenly and affected evidently by the terrain.Although the PEh values in the four typical areas(0.3–0.6)are higher than those in other regions,the CWR is relatively abundant and has a higher exploitation potential.Therefore,it is well-founded to exploit CWR for alleviating water shortages in these areas of Northwest China in summer.
基金Supported by the National Key Research and Development Program of China(2016YFA0601701)National High Technology Research and Development Program of China(2012AA120902)。
文摘The water in the air is composed of water vapor and hydrometeors,which are inseparable in the global atmosphere.Precipitation basically comes from hydrometeors instead of directly from water vapor,but hydrometeors are rarely focused on in previous studies.When assessing the maximum potential precipitation,it is necessary to quantify the total amount of hydrometeors present in the air within an area for a certain period of time.Those hydrometeors that have not participated in precipitation formation in the surface,suspending in the atmosphere to be exploited,are defined as the cloud water resource(CWR).Based on the water budget equations,we defined 16 terms(including 12 independent ones)respectively related to the hydrometeors,water vapor,and total water substance in the atmosphere,and 12 characteristic variables related to precipitation and CWR such as precipitation efficiency(PE)and renewal time(RT).Correspondingly,the CWR contributors are grouped into state terms,advection terms,and source/sink terms.Two methods are developed to quantify the CWR(details of which are presented in the companion paper)with satellite observations,atmospheric reanalysis data,precipitation products,and cloud resolving models.The CWR and related variables over North China in April and August 2017 are thus derived.The results show that CWR has the same order of magnitude as surface precipitation(Ps).The hydrometers converted from water vapor(Cvh)during the condensation process is the primary source of precipitation.It is highly correlated with Ps and contributes the most to the CWR over a large region.The state variables and advection terms of hydrometeors are two orders of magnitude lower than the corresponding terms of water vapor.The atmospheric hydrometeors can lead to higher PE than water vapor(several tens of percent versus a few percent),with a shorter RT(only a few hours versus several days).For daily CWR,the state terms are important,but for monthly and longer-time mean CWR,the source/sink terms(i.e.,cloud microphysical processes)contribute the largest;meanwhile,the advection terms contribute less for larger study areas.
基金Supported by the National Key Research and Development Program of China(2016YFA0601701)National High Technology Research and Development Program of China(2012AA120902)。
文摘Based on the concepts of cloud water resource(CWR)and related variables proposed in the first part of this study,this paper provides details of two methods to quantify the CWR.One is diagnostic quantification(CWR-DQ)based on satellite observations,precipitation products,and atmospheric reanalysis data;and the other is numerical quantification(CWR-NQ)based on a cloud resolving model developed at the Chinese Academy of Meteorological Sciences(CAMS).The two methods are applied to quantify the CWR in April and August 2017 over North China,and the results are evaluated against all available observations.Main results are as follows.(1)For the CWR-DQ approach,reference cloud profiles are firstly derived based on the Cloud Sat/CALIPSO joint satellite observations for 2007–2010.The NCEP/NCAR reanalysis data in 2000–2017 are then employed to produce three-dimensional cloud fields.The budget/balance equations of atmospheric water substance are lastly used,together with precipitation observations,to retrieve CWR and related variables.It is found that the distribution and vertical structure of clouds obtained by the diagnostic method are consistent with observations.(2)For the CWR-NQ approach,it assumes that the cloud resolving model is able to describe the cloud microphysical processes completely and precisely,from which four-dimensional distributions of atmospheric water vapor,hydrometeors,and wind fields can be obtained.The data are then employed to quantify the CWR and related terms/quantities.After one-month continuous integration,the mass of atmospheric water substance becomes conserved,and the tempospatial distributions of water vapor,hydrometeors/cloud water,and precipitation are consistent with observations.(3)Diagnostic values of the difference in the transition between hydrometeors and water vapor(Cvh-Chv)and the surface evaporation(Es)are well consistent with their numerical values.(4)Correlation and bias analyses show that the diagnostic CWR contributors are well correlated with observations,and match their numerical counterparts as well,indicating that the CWR-NQ and CWR-DQ methods are reasonable.(5)Underestimation of water vapor converted from hydrometeors(Chv)is a shortcoming of the CWR-DQ method,which may be rectified by numerical quantification results or by use of advanced observations on higher spatiotemporal resolutions.
基金Supported by the National Key Research and Development Program of China(2016YFA0601701)National High Technology Research and Development Program of China(2012AA120902)。
文摘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.
基金Supported by the National Key Research and Development Program of China(2016YFA0601701)National Natural Science Foundation of China(42075191)National High Technology Research and Development Program of China(2012AA120902).
文摘Based on the concept of cloud water resource(CWR)and the cloud microphysical scheme developed by the Chinese Academy of Meteorological Sciences(CAMS),a coupled mesoscale and cloud-resolving model system is developed in the study for CWR numerical quantification(CWR-NQ)in North China for 2017.The results show that(1)the model system is stable and capable for performing 1-yr continuous simulation with a water budget error of less than 0.2%,which indicates a good water balance.(2)Compared with the observational data,it is confirmed that the simulating capability of the CWR-NQ approach is decent for the spatial distribution of yearly cumulative precipitation,daily precipitation intensity,yearly average spatial distribution of water vapor.(3)Compared with the CWR diagnostic quantification(CWR-DQ),the results from the CWR-NQ differ mainly in cloud condensation and cloud evaporation.However,the deviation of the net condensation(condensation minus evaporation)between the two methods is less than 1%.For other composition variables,such as water vapor advection,surface evaporation,precipitation,cloud condensation,and total atmospheric water substances,the relative differences between the CWR-NQ and the CWR-DQ are less than 5%.(4)The spatiotemporal features of the CWR in North China are also studied.The positive correlation between water vapor convergence and precipitation on monthly and seasonal scales,and the lag of precipitation relative to water vapor convergence on hourly and daily scales are analyzed in detail,indicating the significance of the state term on hourly and daily scales.The effects of different spatial scales on the state term,advection term,source-sink term,and total amount are analyzed.It is shown that the advective term varies greatly at different spatiotemporal scales,which leads to differences at different spatiotemporal scales in CWR and related characteristic quantities.