Unveiling Cloud Vertical Structures over the Interior Tibetan Plateau through Anomaly Detection in Synergetic Lidar and Radar Observations

Cloud vertical structure(CVS)strongly affects atmospheric circulation and radiative transfer.Yet,long-term,groundbased observations are scarce over the Tibetan Plateau(TP)despite its vital role in global climate.This study utilizes ground-based lidar and Ka-band cloud profiling radar(KaCR)measurements at Yangbajain(YBJ),TP,from October 2021 to September 2022 to characterize cloud properties.A satisfactorily performing novel anomaly detection algorithm(LevelShiftAD)is proposed for lidar and KaCR profiles to identify cloud boundaries.Cloud base heights(CBH)retrieved from KaCR and lidar observations show good consistency,with a correlation coefficient of 0.78 and a mean difference of-0.06 km.Cloud top heights(CTH)derived from KaCR match the FengYun-4A and Himawari-8 products well.Thus,KaCR measurements serve as the primary dataset for investigating CVSs over the TP.Different diurnal cycles occur in summer and winter.The diurnal cycle is characterized by a pronounced increase in cloud occurrence frequency in the afternoon with an early-morning decrease in winter,while cloud amounts remain high all day,with scattered nocturnal increases in summer.Summer features more frequent clouds with larger geometrical thicknesses,a higher multi-layer ratio,and greater inter-cloud spacing.Around 26%of the cloud bases occur below 0.5 km.Winter exhibits a bimodal distribution of cloud base heights with peaks at 0-0.5 km and 2-2.5 km.Single-layer and geometrically thin clouds prevail at YBJ.This study enriches long-term measurements of CVSs over the TP,and the robust anomaly detection method helps quantify cloud macro-physical properties via synergistic lidar and radar observations.

Microphysical Characteristics of Rainfall Based on Long-Term Observations with a 2DVD in Yangbajain,Tibet

Raindrop size distribution(DSD)plays a crucial role in enhancing the accuracy of radar quantitative precipitation estimates in the Tibetan Plateau(TP).However,there is a notable scarcity of long-term,high-resolution observations in this region.To address this issue,long-term observations from a two-dimensional video disdrometer(2DVD)were leveraged to refine the radar and satellite-based algorithms for quantifying precipitation in the hinterland of the TP.It was observed that weak precipitation(R<1,mm h-1)accounts for 86%of the total precipitation time,while small raindrops(D<2 mm)comprise 99%of the total raindrop count.Furthermore,the average spectral width of the DSD increases with increasing rain rate.The DSD characteristics of convective and stratiform precipitation were discussed across five different rain rates,revealing that convective precipitation in Yangbajain(YBJ)exhibits characteristics similar to maritime-like precipitation.The constrained relationships between the slopeΛand shapeμ,D_(m)and N_(w)of gamma DSDs were derived.Additionally,we established a correlation between the equivalent diameter and drop axis ratio and found that raindrops on the TP attain a nearly spherical shape.Consequently,the application of the rainfall retrieval algorithms of the dual-frequency precipitation radar in the TP is improved based on the statistical results of the DSD.

Assessment of FY-4A and Himawari-8 Cloud Top Height Retrieval through Comparison with Ground-Based Millimeter Radar at Sites in Tibet and Beijing

The accuracy of passive satellite cloud top height (CTH) retrieval shows regional dependence. This paper assesses the CTH derived from the FY-4A and Himawari-8 satellites through comparison with those from the ground-based millimeter radar at two sites: Yangbajing, Tibet, China (YBJ), and the Institute of Atmospheric Physics (IAP), Beijing, China. The comparison shows that Himawari-8 missed more CTHs at night than FY-4A, especially at YBJ. It is found that the CTH difference (CTHD;radar CTH minus satellite CTH) for FY-4A and Himawari-8 is 0.06 ± 1.90 km and −0.02 ± 2.40 km at YBJ respectively, and that is 0.93 ± 2.24 km and 0.99 ± 2.37 km at IAP respectively. The discrepancy between the satellites and radar at IAP is larger than that at YBJ. Both satellites show better performance for mid-level and low-level clouds than for high-level clouds at the two sites. The retrievals from FY-4A agree well with those from Himawari-8, with a mean difference of 0.08 km at YBJ and 0.06 km at IAP. It is found that the CTHD decreases as the cloud depth increases at both sites. However, the CTHD has no obvious dependence on cloud layers and fractions. Investigations show that aerosol concentration has little impact on the CTHD. For high and thin clouds, the CTHD increases gradually with the increase of the surface temperature, which might be a key factor causing the regional discrepancy between IAP and YBJ.

The First Global Carbon Dioxide Flux Map Derived from TanSat Measurements

Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon surface fluxes inferred from dry-air CO_2 column (XCO_2) measurements by the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (Tan Sat) are presented.An ensemble transform Kalman filter (ETKF) data assimilation system coupled with the GEOS-Chem global chemistry transport model is used to optimally fit model simulations with the Tan Sat XCO_2 observations,which were retrieved using the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS).High posterior error reduction (30%–50%) compared with a priori fluxes indicates that assimilating satellite XCO_2 measurements provides highly effective constraints on global carbon flux estimation.Their impacts are also highlighted by significant spatiotemporal shifts in flux patterns over regions critical to the global carbon budget,such as tropical South America and China.An integrated global land carbon net flux of 6.71±0.76 Gt C yr^(-1) over12 months (May 2017–April 2018) is estimated from the Tan Sat XCO_2 data,which is generally consistent with other inversions based on satellite data,such as the JAXA GOSAT and NASA OCO-2 XCO_2 retrievals.However,discrepancies were found in some regional flux estimates,particularly over the Southern Hemisphere,where there may still be uncorrected bias between satellite measurements due to the lack of independent reference observations.The results of this study provide the groundwork for further studies using current or future Tan Sat XCO_2 data together with other surfacebased and space-borne measurements to quantify biosphere–atmosphere carbon exchange.

A New TanSat XCO2 Global Product towards Climate Studies

The 1st Chinese carbon dioxide(CO2)monitoring satellite mission,TanSat,was launched in 2016.The 1st TanSat global map of CO2 dry-air mixing ratio(XCO2)measurements over land was released as version 1 data product with an accuracy of 2.11 ppmv(parts per million by volume).In this paper,we introduce a new(version 2)TanSat global XCO2 product that is approached by the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing(IAPCAS),and the European Space Agency(ESA)Climate Change Initiative plus(CCI+)TanSat XCO2 product by University of Leicester Full Physics(UoL-FP)retrieval algorithm.The correction of the measurement spectrum improves the accuracy(−0.08 ppmv)and precision(1.47 ppmv)of the new retrieval,which provides opportunity for further application in global carbon flux studies in the future.Inter-comparison between the two retrievals indicates a good agreement,with a standard deviation of 1.28 ppmv and a bias of−0.35 ppmv.

A New Global Solar-induced Chlorophyll Fluorescence(SIF)Data Product from TanSat Measurements

The Chinese Carbon Dioxide Observation Satellite Mission(TanSat)is the third satellite for global CO2 monitoring and is capable of detecting weak solar-induced chlorophyll fluorescence(SIF)signals with its advanced technical characteristics.Based on the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing(IAPCAS)platform,we successfully retrieved the TanSat global SIF product spanning the period of March 2017 to February 2018 with a physically based algorithm.This paper introduces the new TanSat SIF dataset and shows the global seasonal SIF maps.A brief comparison between the IAPCAS TanSat SIF product and the data-driven SVD(singular value decomposition)SIF product is also performed for follow-up algorithm optimization.The comparative results show that there are regional biases between the two SIF datasets and the linear correlations between them are above 0.73 for all seasons.The future SIF data product applications and requirements for SIF space observation are discussed.

The TanSat mission： preliminary global observations

The Chinese global carbon dioxide monitoring satellite （TanSat） was launched successfully in December 2016 and has completed its on-orbit tests and calibration. TanSat aims to measure the atmospheric column-averaged dry air mole fractions of carbon dioxide （XCO2） with a precision of 4 ppm at the regional scale, and in addition, to derive global and regional CO2 fluxes. Progress towards these objectives is reviewed and the first scientific results from TanSat measurements are presented. TanSat on-orbit tests indicate that the Atmospheric Carbon dioxide GratingSpectrometer is in normal working status and is beginning to produce LIB products. The preliminary TanSat XCO2 products have been retrieved by an algorithm and compared to NASA Orbiting Carbon Observatory-2 （OCO-2） measurements during an over- lapping observation period. Furthermore, the XCO2 retrievals have been validated against eight groundsite measurement datasets from the Total Carbon Column Observing Network, for which the preliminary conclusion is that TanSat has met the precision design requirement, with an average bias of 2.11 ppm. The first scientific observations are presented, namely, the seasonal distributions of XCO2 over land on a global scale.