【作者】 梁宏；

【导师】 张人禾； 刘晶淼；

【作者基本信息】 中国气象科学研究院 ， 气象学， 2012， 博士

【摘要】 本论文基于多源大气水汽资料（地基GPS、探空和数值模式输出），采用多种研究方法以及大气辐射模式，探讨了青藏高原（简称高原，下同）大气水汽多时间尺度变化特征及其对辐射模拟的影响。结果表明：（1）近10多年（1999～2010）拉萨探空（RS）观测的大气水汽总量（PW）比地基GPS观测的结果（GPS_PW）明显偏小，偏小程度随使用不同的探空仪而异，新型探空仪（GTS-1）的探测偏差明显小于旧型探空仪（GZZ-2）的探测偏差。分析发现PW偏差（RS_PW-GPS_PW）具有明显季节变化和日变化特征。太阳辐射加热以及气温日变化和季节变化是造成PW偏差日变化和季节变化的原因。据此提出了PW偏差的订正方法，该方法在实际应用中取得了较好订正效果。（2）近35年（1976～2010年）高原PW和大气平均温度均呈显著增加趋势，大气增温是PW增加的重要因素。在高原夏季风活跃期（4月上旬～10下旬）PW具有4～14天和60～90天的显著变化周期。夏季高原及周边地区的季风区和季风边缘区PW随海拔高度的变化符合幂函数规律。高原PW具有显著日变化特征，该特征随站点海拔高度、地形和局地气候特点的不同而异。（3）基于降水临界理论，建立了PW和降水量之间的关系式。在高原大气增温和增湿的背景下，极端降水发生频率增加。（4）高原地区ECMWF分析资料的PW与GPS_PW基本一致，JRA-25分析资料的PW在夏季略偏小。NCEP和Met-Office分析资料的PW夏季明显偏小，这些大气水汽估算误差对高原长短波辐射模拟均有重要影响。（5）高原大气水汽、臭氧、气溶胶和云对太阳辐射直接影响呈显著季节变化特征。水汽对太阳辐射吸收月平均值约9～95W/m~2，约占太阳总辐射2%～13%。臭氧对太阳辐射吸收月平均值约8～12W/m~2，约占太阳总辐射1.5%～1.8%。气溶胶对太阳辐射直接影响为春夏季较强，秋冬季较弱。高原气溶胶直接辐射强迫年平均值约-13.7~-10.1W/m~2。云对地表短波辐射强迫年平均值约70～140W/m~2，其大小与站点所处区域的气候特征有关。高原大气水汽、臭氧和云对向下长波辐射的影响也呈显著季节变化特征。大气水汽向下发射的长波辐射约10～78W/m~2，约占地表向下长波辐射6.0%～25.0%。臭氧向下发射的长波辐射约1.6～2.0W/m~2，约占地表向下长波辐射0.6%～1.0%。云对向下长波辐射影响的年平均值约20～40W/m~2。近35年高原夏季水汽增加对太阳总辐射、净短波辐射和长波辐射的影响分别为-1.16±0.40、-0.93±0.32和1.28W m-2/10a。年平均水汽增加对太阳总辐射、净短波辐射和长波辐射的影响分别为-0.57±0.18、-0.45±0.14和0.65W m-2/10a。更多还原

【Abstract】 Based on a variety of different sources of precipitable water vapor (PW) data (ground-basedGPS, radiasonde and numerical weather prediction system analysis), the variations of PW withmultiple time scales and their causes on the Tibetan Plateau (TP) are analyzed using a varietyof different sources of methods. The radiative effects of atmospheric water vapor and otheratmospheric compositions are investigated using radiative models. The results show that (1) theradiosonde (RS) PW is significant dryer than that derived by ground-based GPS (GPS_PW) atLhasa on TP during a period of more than one decade. Different types of radiosonde humiditysensors show different magnitude of the dry bias of PW. The RS_PW dry bias by GZZ-2(goldbeater’s skin hygrometer) is more significant than that by GTS-1(carbon hygristor). Thetemporal variation characteristics of the RS_PW dry bias are also investigated. The resultsshow that RS_PW dry bias exhibited pronounced diurnal and annual variations. The solarradiative heating to the humidity sensors may have played an important role in the RS_PW drybias diurnal and annual variability. It can be seen that the diurnal variations of RS_PW dry biasare significant also partly because air temperature is higher at1200UTC than that at0000UTC.The annual variations of RS_PW dry bias are pronounced also partly because air temperature ishigher in summer than that in winter. The calibration methods for the RS_PW dry bias aredeveloped and applied to the GZZ-2and GTS-1sounding PW datasets at Lhasa and Naqu. Thecorrections greatly improve the accuracy of the RS_PW.(2) For long-term changes, the PWand atmospheric mean temperature increased significantly on TP during recent35years (from1976to2010). The increasing trend in PW may be due to the increase in atmospherictemperature during the recent35years. For seasonal changes, PW time series shows variationswith4–14days and60–90days periods during summer monsoon seasons (from early April tolate October). The relationship between PW and sites altitudes can be fitted well using a powerlaw function. For diurnal variation, PW exhibited a pronounced diurnal variation over the TPand its around areas. The characteristics of PW diurnal variation vary with the different sitealtitude, terrain and local climate characteristics.(3) Based on critical phenomena inatmospheric precipitation, the relationship of PW and hourly precipitation is fitted as a powerlaw function. Extreme precipitation probability may increase with the significant increase ofPW and air temperature on TP.(4) The PW comparison between numerical weather model(NWP) system analysis (ECMWF, NCEP, JRA-25, and Met-office) and GPS data reveals that the PW within ECMWF reanalysis data agrees very well with that derived from ground-basedGPS. The PW within JRA-25reanalysis data is slightly underestimated on summer seasons.However, The PW within NCEP reanalysis and NWP output from Met-office have significantdry bias in summer seasons. The effect of the PW differences on surface radiation budget isevaluated using a radiation model. The results show that radiative flux at the surfacedetermined using the model analysis profiles with the water vapor corrected by PWobservations are closer to the observations compared with those without water vapor correction.The radiative flux differences at the surface with and without water vapor correction are largerthan that caused by doubling the concentration of carbon dioxide in the atmosphere in thisregion.(5) The effects of water vapor, ozone, aerosol and cloud on solar radiation exhibitpronounced seasonal variability. The monthly mean solar radiation absorbed by water vapor isabout9~95W/m~2, namely about2%~13%of the global solar radiation. The monthly meansolar radiation absorbed by ozone is about8~12W/m~2, namely about1.51%~1.78%of theglobal solar radiation. The aerosol direct radiative forcing (ADRF) for solar radiation is peak insummer and lowest in winter. The annual mean ADRF is-13.7~-10.1W/m~2. The annual meanCRF is from70W/m~2to140W/m~2and varies with local climate characteristics. The effects ofwater vapor, ozone, and cloud on longwave radiation also exhibit pronounced seasonalvariability. The monthly mean values of the effect is10~78W/m~2, namely6.0%~25.0%of thedownward longwave flux at the surface. The monthly mean value of the effect is1.6～2.0W/m~2, namely about0.6%～1.0%of the downward longwave flux at the surface. The annualmean cloud radiative forcing (CLRF) is from20W/m~2to40W/m~2and varies with localclimate characteristics. Since the seasonal mean PW on summer and the annual mean PWincrease significantly during the period from1976to2010, the seasonal mean global and netsolar radiation on summer decrease with changing rates of-1.16±0.40and-0.93±0.32W m-2/10a respectively. The seasonal mean downward longwave flux on summer increaseswith a changing rate of1.28W m-2/10a. The annual mean global and net solar radiationdecrease with changing rates of-0.57±0.18and-0.45±0.14W m-2/10a respectively. The annualmean downward longwave flux increases with a changing rate of0.65W m-2/10a.更多还原