[1] Two analysis schemes are developed within an off-line version of the land surface scheme ISBA for the initialization of soil water content and temperature in numerical weather prediction models. The first soil analysis is based on optimal interpolation that is currently operational in a number of weather centers. The second soil analysis is an extended Kalman filter (EKF) which will allow the assimilation of satellite observations. First, it is shown, by comparing the Kalman gain of both analysis schemes, that it is possible to assimilate screen level temperature and relative humidity in an off-line system. This is of great interest for future combined assimilations of conventional and satellite data. The reduced computing time in running the land surface scheme outside the atmospheric model makes Kalman filter approaches compatible with operational requirements. The methodology for coupling the land surface data assimilation with the atmospheric analysis system is explained in order to highlight the existing feedbacks between the two systems (in comparison to fully decoupled land data assimilation systems). The linearity of the observation operator Jacobians estimated by finite differences and the relevance of the soil prognostic variables to be initialized are assessed. Finally, the two systems are compared over western Europe for the month of July 2006 by assimilating screen level temperature and relative humidity every 6 h. The EKF has been simplified by keeping the covariance matrix of background errors constant. The two soil analysis schemes behave similarly in response to screen level atmospheric errors. The EKF is superior in identifying situations where the near-surface atmosphere is sensitive to soil perturbations, which leads to better use of observations. Over France, the capability of both systems to moisten the soil when rain events are absent from the forcing is demonstrated.
Capsule Summary We found a range of user needs to inform the development of drought monitoring and early warning systems in four countries in the Middle East and North Africa (MENA) region through engagement with governmental, academic, civil society, private sector, and international organizations.
36Many regions in Africa and the Middle East are vulnerable to drought and to 37 water and food insecurity, motivating agency efforts such as the U.S. Agency for 38 International Development's (USAID) Famine Early Warning Systems Network (FEWS 39 NET) to provide early warning of drought events in the region. Each year these 40 warnings guide life-saving assistance that reaches millions of people. A new NASA 41 multi-model, remote sensing-based hydrological forecasting and analysis system, 42NHyFAS, has been developed to support such efforts by improving the FEWS NET's 43 current early warning capabilities. NHyFAS derives its skill from two sources: (i) 44 accurate initial conditions, as produced by an offline land modeling system through the 45 application and/or assimilation of various satellite data (precipitation, soil moisture, and 46 terrestrial water storage); and (ii) meteorological forcing data during the forecast period 47 as produced by a state-of-the-art ocean-land-atmosphere forecast system. The land 48 modeling framework used is the Land Information System (LIS), which employs a suite 49 of land surface models, allowing multi-model ensembles and multiple data assimilation 50 strategies to better estimate land surface conditions. An evaluation of NHyFAS shows 51 that its one-to-five month hindcasts successfully capture known historic drought events, 52 and it has improved skill over benchmark type hindcasts. The system also benefits from 53 strong collaboration with end-user partners in Africa and the Middle East, who provide 54 insights on strategies to formulate and communicate early warning indicators to water 55 and food security communities. The additional lead time provided by this system will 56 increase the speed, accuracy and efficacy of humanitarian disaster relief, helping to 57 save lives and livelihoods. 58 Capsule Summary: The new NASA Hydrological Forecast and Analysis System 60 (NHyFAS) provides multi-model seasonal forecasts of hydrological and agricultural 61 drought to end-users, such as the Famine Early Warning Systems Network. 62
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.