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Global distributions of CO2 volume mixing ratio in the middle and upper atmosphere from daytime MIPAS high-resolution spectra

机译:从白天MIPAS高分辨率光谱看中高层大气中CO2体积混合比的全球分布

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摘要

Global distributions of the CO vmr (volume mixing ratio) in themesosphere and lower thermosphere (from 70 up to  ∼  140 km) have beenderived from high-resolution limb emission daytime MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) spectra inthe 4.3 µm region. This is the first time that the CO vmr hasbeen retrieved in the 120–140 km range. The data set spans from January2005 to March 2012. The retrieval of CO has been performed jointly withthe elevation pointing of the line of sight (LOS) by using a non-localthermodynamic equilibrium (non-LTE) retrieval scheme. The non-LTE modelincorporates the new vibrational–vibrational and vibrational–translationalcollisional rates recently derived from the MIPAS spectra by[Jurado-Navarro et al.(2015)]. It also takes advantage of simultaneous MIPASmeasurements of other atmospheric parameters (retrieved in previous steps),such as the kinetic temperature (derived up to  ∼  100 km from theCO 15 µm region of MIPAS spectra and from 100 up to 170 kmfrom the NO 5.3 µm emission of the same MIPAS spectra) and theO measurements (up to  ∼  100 km). The latter is very important forcalculations of the non-LTE populations because it strongly constrains theO() and O() concentrations below  ∼  100 km. The estimatedprecision of the retrieved CO vmr profiles varies with altitude rangingfrom  ∼  1 % below 90 km to 5 % around 120 km and larger than10 % above 130 km. There are some latitudinal and seasonal variations ofthe precision, which are mainly driven by the solar illumination conditions.The retrieved CO profiles have a vertical resolution of about 5–7 km below120 km and between 10 and 20 km at 120–140 km. We have shown that theinclusion of the LOS as joint fit parameter improves the retrieval ofCO, allowing for a clear discrimination between the information onCO concentration and the LOS and also leading to significantly smallersystematic errors. The retrieved CO has an improved accuracy because ofthe new rate coefficients recently derived from MIPAS and the simultaneousMIPAS measurements of other key atmospheric parameters (retrieved in previoussteps) needed for non-LTE modelling like kinetic temperature and Oconcentration. The major systematic error source is the uncertainty of thepressure/temperature profiles, inducing errors at midlatitude conditions ofup to 15 % above 100 km (20 % for polar summer) and of ∼  5 % around 80 km. The errors due to uncertainties in theO() and O() profiles are within 3–4 % in the 100–120 kmregion, and those due to uncertainties in the gain calibration and in thenear-infrared solar flux are within ∼  2 % at all altitudes. The retrieved CO shows the majorfeatures expected and predicted by general circulation models. In particular,its abrupt decline above 80–90 km and the seasonal change of thelatitudinal distribution, with higher CO abundances in polar summer from70 up to  ∼  95 km and lower CO vmr in the polar winter. Above ∼  95 km, CO is more abundant in the polar winter than at themidlatitudes and polar summer regions, caused by the reversal of the meancirculation in that altitude region. Also, the solstice seasonaldistribution, with a significant pole-to-pole CO gradient, lasts about2.5 months in each hemisphere, while the seasonal transition occurs quickly.
机译:在大气层和低热层(从70到140 km)中,CO vmr(体积混合比)的全球分布已从4.3?µm区域中的高分辨率肢体白天白天MIPAS(无源大气米歇尔森干涉仪)光谱中得出。这是首次在120–140 km范围内检索到CO vmr。该数据集的时间跨度为2005年1月至2012年3月。CO的检索是通过使用非局部热力学平衡(non-LTE)检索方案与视线高程(LOS)一起进行的。非LTE模型结合了最近从MIPAS光谱得出的新的振动-振动和振动-平移碰撞率[Jurado-Navarro et al。(2015)]。它还利用了同时进行其他大气参数的MIPAS测量(在先前步骤中进行了测量),例如动力学温度(从MIPAS光谱的CO 15 regionm区域到〜100 km,从5.3 µm的发射到100 170 km。相同的MIPAS光谱)和O的测量值(最大〜100 km)。后者对于非LTE人口的计算非常重要,因为它强烈限制了〜)100 km以下的O()和O()浓度。所获取的CO vmr剖面的估计精度随高度的变化而变化,范围从90 km以下的〜1%到120 km附近的5%,大于130 km以上的10%。精度存在一些纬度和经度变化,这主要是由太阳光照条件引起的。所获取的CO剖面的垂直分辨率约为120 km以下5–7 km,120 120140km处的垂直分辨率在10至20 km之间。我们已经表明,将LOS作为联合拟合参数包括在内可以改善CO的检索,从而可以清楚地区分CO浓度信息和LOS,并且还可以显着减小系统误差。由于最近从MIPAS导出了新的速率系数,并且同时对非LTE建模所需的其他关键大气参数(如先前步骤中获得的)进行了MIPAS测量(如动力学温度和O浓度),因此检索到的CO具有更高的精度。系统误差的主要来源是压力/温度曲线的不确定性,在中纬度条件下引起的误差最高可达100 km以上15%(极地夏季高达20%)和80 km左右5%。由于O()和O()轮廓的不确定性导致的误差在100-120 km范围内在3-4%之内,而由于增益校准和红外红外光通量的不确定性所造成的误差在2%之内。海拔。检索到的CO显示了一般循环模型预期和预测的主要特征。尤其是在80-90 km以上突然下降,并随纬向分布的季节变化而变化,极地夏季的CO丰度较高,从70至95 km,极地冬季的CO vmr较低。高于95 km时,极地冬季的CO含量高于中纬度和极地夏季地区,这是由于该海拔地区的平均环流逆转所致。而且,冬至的季节分布具有极高的极间CO梯度,在每个半球持续约2.5个月,而季节性过渡迅速发生。

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