Reichle Rolf H, Zhang Sara Q, Liu Qing, Draper Clara S, Kolassa Jana, Todling Ricardo
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA.
Physical Sciences Laboratory, NOAA Earth System Research Laboratories, Boulder, CO 80305 USA.
IEEE J Sel Top Appl Earth Obs Remote Sens. 2021;14:10628-10643. doi: 10.1109/jstars.2021.3118595. Epub 2021 Oct 7.
Errors in soil moisture adversely impact the modeling of land-atmosphere water and energy fluxes and, consequently, near-surface atmospheric conditions in atmospheric data assimilation systems (ADAS). To mitigate such errors, a land surface analysis is included in many such systems, although not yet in the currently operational NASA Goddard Earth Observing System (GEOS) ADAS. This article investigates the assimilation of L-band brightness temperature (Tb) observations from the Soil Moisture Active Passive (SMAP) mission in the GEOS weakly coupled land-atmosphere data assimilation system (LADAS) during boreal summer 2017. The SMAP Tb analysis improves the correlation of LADAS surface and root-zone soil moisture versus measurements by ~0.1-0.26 over that of ADAS estimates; the unbiased root-mean-square error of LADAS soil moisture is reduced by 0.002-0.008 m/m from that of ADAS. Furthermore, the global land average RMSE versus measurements of screen-level air specific humidity (q2m) and daily maximum temperature (T2m) is reduced by 0.05 g/kg and 0.04 K, respectively, for LADAS compared to ADAS estimates. Regionally, the RMSE of LADAS q2m and T2m is improved by up to 0.4 g/kg and 0.3 K, respectively. Improvement in LADAS specific humidity extends into the lower troposphere (below ~700 mb), with relative improvements in bias of 15-25%, although LADAS air temperature bias slightly increases relative to that of ADAS. Finally, the root mean square of the LADAS Tb observation-minus-forecast residuals is smaller by up to ~0.1 K than in a land-only assimilation system, corroborating the positive impact of the Tb analysis on the modeled land-atmosphere coupling.
土壤湿度误差会对陆-气水和能量通量的建模产生不利影响，进而影响大气数据同化系统（ADAS）中的近地表大气状况。为了减轻此类误差，许多此类系统都包含了陆面分析，不过目前运行的美国国家航空航天局戈达德地球观测系统（GEOS）ADAS尚未包含。本文研究了2017年北半球夏季，在GEOS弱耦合陆-气数据同化系统（LADAS）中对土壤湿度主动被动探测（SMAP）任务的L波段亮温（Tb）观测数据进行同化的情况。与ADAS估算相比，SMAP Tb分析将LADAS表层和根区土壤湿度与测量值之间 的相关性提高了约0.1-0.26；LADAS土壤湿度的无偏均方根误差比ADAS降低了0.002-0.008 m/m。此外，与ADAS估算相比，LADAS的全球陆地平均与测量值的均方根误差，对于近地面空气比湿（q2m）和日最高温度（T2m）分别降低了0.05 g/kg和0.04 K。在区域上，LADAS的q2m和T2m的均方根误差分别最多提高了0.4 g/kg和0.3 K。LADAS比湿的改善延伸到了对流层下部（约700百帕以下），偏差相对改善了15-25%，不过LADAS气温偏差相对于ADAS略有增加。最后，LADAS Tb观测值减去预报值残差的均方根比仅陆地同化系统小了约0.1 K，证实了Tb分析对模拟陆-气耦合的积极影响。
