基于专家场模型FoEs的安徽省GPS/PWV资料插补初步研究
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摘要
由于GPS/PWV资料在短时和临近天气预报、人工影响天气和空中水资源研究中具有潜在应用价值。考虑到GPS/PWV资料存在较多缺测,文中基于专家场模型(Fields of Experts,FoEs)进行了GPS/PWV资料插补初步研究。采用交叉验证法检验了常用插值方法(临近点、线性、三次样条和立方插值法)和FoEs插补GPS/PWV的精度,得到的FoEs模型插补精度较高。进一步给出了FoEs插补GPS/PWV连续缺测资料,解决了常用插值法无法对连续缺测资料有效插值的问题,为其它资料插补提供了新的思路。
Because of the GPS/PWV data has potential application value in the research of short-term weather forecast,weather modification and the air to water resources research.Considering the loss data of GPS/PWV,this paper preliminary studies on the interpolation of GPS/PWV data based on the fields of experts model FoEs.Using cross validation method,the precision of commonly interpolation method(nearest,linear,spline and cubic)and FoEs interpolated GPS/PWV are tested.And the FoEs model interpolation possesses of higher accuracy.When exists continuous loss data,the interpolation experiments of GPS/PWV data using FoEs are further given out.It can solve the problem of common interpolation method that cannot work in continuous loss data.The FoEs maybe offer a new interpolation idea for the other data.
Because of the GPS/PWV data has potential application value in the research of short-term weather forecast,weather modification and the air to water resources research.Considering the loss data of GPS/PWV,this paper preliminary studies on the interpolation of GPS/PWV data based on the fields of experts model FoEs.Using cross validation method,the precision of commonly interpolation method(nearest,linear,spline and cubic)and FoEs interpolated GPS/PWV are tested.And the FoEs model interpolation possesses of higher accuracy.When exists continuous loss data,the interpolation experiments of GPS/PWV data using FoEs are further given out.It can solve the problem of common interpolation method that cannot work in continuous loss data.The FoEs maybe offer a new interpolation idea for the other data.
引文
[1]李延兴,徐宝祥,胡新康,等.应用地基GPS技术遥感大气柱水汽量的实验研究[J].应用气象学报,2001,12(1):61-68.
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[3]毕研盟,毛节泰,毛辉.海南GPS网探测对流层水汽廓线的试验研究[J].应用气象学报,2008,19(4):412-419.
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[9]李延兴,徐宝祥,胡新康,等.用地基GPS观测站遥测大气含水量和可降雨量的理论基础与试验结果[J].中国科学:数学,2000,30(S1):107-110.
[10]陈娇娜,李国平,黄文诗.成都地区秋、冬季GPS可降水量的时空分析[J].气象科学,2009,29(5):682-686.
[11]吴建军,王鑫,吕达仁等.北京可降水量变化特征的地基GPS观测与分析[J].大气科学学报,2007,30(3):377-382.
[12]罗梦森,曾明剑,景元书,等.GPS反演的大气可降水量变化特征及其与降水的关系研究[J].气象科学,2013,33(4):418-423.
[13]曹晓刚,丁金才,叶其欣,等.利用水汽总量资料诊断入梅时间的方法[J].应用气象学报,2007,18(6):791-801.
[14]杨红梅,何平,徐宝祥.用GPS资料分析华南暴雨的水汽特征[J].气象,2002,28(5):17-21.
[15]郭洁,李国平,黄文诗.GPS可降水量与大雾天气关系的初步分析[J].自然灾害学报,2011,20(4):142-146.
[16]张斌,薛根元,张双成.基于IGS超级跟踪站近实时解算浙江地基GPS大气可降水量[J].热带气象学报,2009,25(2):222-226.
[17]ROTH S,BLACK M J.Fields of experts[J].International Journal of Computer Vision,2009,82(2):205-229.
[18]ROTH S,BLACK M J.Fields of Experts:A Framework for Learning Image Priors[C]//IEEE Computer Society Conference on Computer Vision&Pattern Recognition,2005:860-867.
[19]徐大宏,王润生.空间结构自适应的图像复原模型[J].计算机工程与应用,2010,46(3):179-182.
[2]陈世范.GPS气象观测应用的研究与展望[J].气象学报,1999,57(2):242-252.
[3]毕研盟,毛节泰,毛辉.海南GPS网探测对流层水汽廓线的试验研究[J].应用气象学报,2008,19(4):412-419.
[4]丁金才.GPS气象学及其应用[M].北京:气象出版社.2009.
[5]BEVIS M,BUSINGER S,HERRING T A,et al.GPS meteorology:Remote sensing of atmospheric water vapor using the global positioning system[J].Journal of Geophysical Research Atmospheres,1992,97(D14):15787-15801.
[6]郭志梅.利用地基GPS资料反演大气可降水量的初步研究[D].南京:南京信息工程大学.2005.
[7]刘红燕,王迎春,王京丽,等.由地基微波辐射计测量得到的北京地区水汽特性的初步分析[J].大气科学,2009,33(2):388-396.
[8]王继竹,郭英莲,徐桂荣,等.湖北省不同资料反演大气可降水量的误差分析[J].气象,2014,40(11):1308-1315.
[9]李延兴,徐宝祥,胡新康,等.用地基GPS观测站遥测大气含水量和可降雨量的理论基础与试验结果[J].中国科学:数学,2000,30(S1):107-110.
[10]陈娇娜,李国平,黄文诗.成都地区秋、冬季GPS可降水量的时空分析[J].气象科学,2009,29(5):682-686.
[11]吴建军,王鑫,吕达仁等.北京可降水量变化特征的地基GPS观测与分析[J].大气科学学报,2007,30(3):377-382.
[12]罗梦森,曾明剑,景元书,等.GPS反演的大气可降水量变化特征及其与降水的关系研究[J].气象科学,2013,33(4):418-423.
[13]曹晓刚,丁金才,叶其欣,等.利用水汽总量资料诊断入梅时间的方法[J].应用气象学报,2007,18(6):791-801.
[14]杨红梅,何平,徐宝祥.用GPS资料分析华南暴雨的水汽特征[J].气象,2002,28(5):17-21.
[15]郭洁,李国平,黄文诗.GPS可降水量与大雾天气关系的初步分析[J].自然灾害学报,2011,20(4):142-146.
[16]张斌,薛根元,张双成.基于IGS超级跟踪站近实时解算浙江地基GPS大气可降水量[J].热带气象学报,2009,25(2):222-226.
[17]ROTH S,BLACK M J.Fields of experts[J].International Journal of Computer Vision,2009,82(2):205-229.
[18]ROTH S,BLACK M J.Fields of Experts:A Framework for Learning Image Priors[C]//IEEE Computer Society Conference on Computer Vision&Pattern Recognition,2005:860-867.
[19]徐大宏,王润生.空间结构自适应的图像复原模型[J].计算机工程与应用,2010,46(3):179-182.