# Performance Evaluation for China's Planned CO\({}_{2}\)-Ipda
## 1 Introduction  
Recent studies show that half of the predicted anthropogenic CO\({}_{2}\) is missing for unknown reasons, resulting in a high level of uncertainty in carbon partitioning models [1, 2]. Therefore, detailed observations of surface and columnar CO\({}_{2}\) concentrations are urgently required to provide better constraints for atmospheric inversions of carbon sinks and sources [3, 4]. Since 2000, several instruments and satellites that use passive remote sensing techniques to retrieve CO\({}_{2}\) concentrations have been sent into orbit, including the Atmospheric Infrared Sounder (AIRS), Scanning Imaging Absorption Spectrometer for Atmospheric Chatography (SCIAMACHY), IASI, Greenhouse GasesObserving Satellite (GOSAT), Orbiting Carbon Observatory-2 (OCO-2), and TanSat. Data acquired by these pioneer satellites have deepened our understanding of the carbon cycle despite their susceptibility to sources of bias and insufficient coverage over high-latitude zones [5; 6; 7; 8; 9]. In the last decade, differential absorption lidar (DIAL) has shown significant promise in atmospheric CO\({}_{2}\) sensing owing to remarkable developments in both the lasers and detectors [10]. Integrated path differential absorption lidar (IPDA), a special type of DIAL, can measure CO\({}_{2}\) concentrations with a high precision and improved coverage, and has been widely adopted by several research groups as a next-generation CO\({}_{2}\) sensor [10; 11; 12; 13; 14]. In recent years, airborne CO\({}_{2}\)-IPDAs have been extensively tested by different research groups funded by the National Aeronautics and Space Administration (NASA) [15; 16; 17; 18; 19; 20; 21]. In these experiments, researchers have claimed to observe ideal results (i.e., results with random errors below 1%) and are anticipating the realization of space-based CO\({}_{2}\)-IPDA in the near future. In 2008, researchers funded by the European Space Agency (ESA) published a report in which concepts, objectives, and requirements for a space-based CO\({}_{2}\)-IPDA were clarified for the first time [22]. In the same year, [PERSON] et al. carried out a sensitivity analysis to illuminate the specific parameter requirements for hardware (e.g., the laser, detector, telescope) [23]. [PERSON] et al. conducted a simulation study on the Active Sensing of CO\({}_{2}\) Emissions over Nights, Days and Seasons (ASCENDS) [24]. Additionally, similar studies have reported results for space-based methane lidar missions [25; 26]. These studies have laid a good theoretical basis for the development of satellite-borne CO\({}_{2}\)-IPDA and indicate a promising future for active remote sensing of greenhouse gas concentrations. Following the Unite States and other developed countries, China is interested in developing its own CO\({}_{2}\)-DIAL or IPDA. A space-based CO\({}_{2}\)-IPDA has been developed to the demonstration stage in China. Unlike NASA's program, which placed different sensors on different satellites and realized near- simultaneous observations of a wide variety of parameters through a coordinated group of satellites (A-train) [27], China's program plans to place multiple sensors, including a CO\({}_{2}\)-IPDA, a Mie-LIDAR, a wide imaging spectrometer, a multi-angle polarization imager, and a polarization scanner, on a single satellite. This configuration will undoubtedly enhance the consistency of the observations from different sensors, but also will pose greater challenges, such as the allocation of power and space, in their design. The satellite orbit and transit time are set at 705 km and 1:00 a.m./1:00 p.m. Local Standard Time (LST), respectively, to provide similar conditions to other passive sensors; this differs from the orbit and time used by ASCENDS (450 km, 6:00 a.m./6:00 p.m. LST). This type of design will have a negative impact on the signal-to-noise ratio of the IPDA load. We need to quantitatively determine the extent to which these parameter settings will impact the accuracy of CO\({}_{2}\) concentration retrievals.