Martin Hirschi

A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System

Abstract The Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) is used operationally in the Integrated Forecast System (IFS) for describing the evolution of soil, vegetation, and snow over the continents at diverse spatial resolutions. A revised land surface hydrology (H-TESSEL) is introduced in the ECMWF operational model to address shortcomings of the land surface scheme, specifically the lack of surface runoff and the choice of a global uniform soil texture. New infiltration and runoff schemes are introduced with a dependency on the soil texture and standard deviation of orography. A set of experiments in stand-alone mode is used to assess the improved prediction of soil moisture at the local scale against field site observations. Comparison with basin-scale water balance (BSWB) and Global Runoff Data Centre (GRDC) datasets indicates a consistently larger dynamical range of land water mass over large continental areas and an improved prediction of river runoff, while the effect on atmospheric...

Soil Control on Runoff Response to Climate Change in Regional Climate Model Simulations

Simulations with seven regional climate models driven by a common control climate simulation of a GCM carried out for Europe in the context of the (European Union) EU-funded Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project were analyzed with respect to land surface hydrology in the Rhine basin. In particular, the annual cycle of the terrestrial water storage was compared to analyses based on the 40-yr ECMWF Re-Analysis (ERA-40) atmospheric convergence and observed Rhine discharge data. In addition, an analysis was made of the partitioning of convergence anomalies over anomalies in runoff and storage. This analysis revealed that most models underestimate the size of the water storage and consequently overestimated the response of runoff to anomalies in net convergence. The partitioning of these anomalies over runoff and storage was indicative for the response of the simulated runoff to a projected climate change consistent with the greenhouse gas A2 Synthesis Report on Emission Scenarios (SRES). In particular, the annual cycle of runoff is affected largely by the terrestrial storage reservoir. Larger storage capacity leads to smaller changes in both wintertime and summertime monthly mean runoff. The sustained summertime evaporation resulting from larger storage reservoirs may have a noticeable impact on the summertime surface temperature projections.

Seasonal Variations in Terrestrial Water Storage for Major Midlatitude River Basins

Abstract This paper presents a new diagnostic dataset of monthly variations in terrestrial water storage for 37 midlatitude river basins in Europe, Asia, North America, and Australia. Terrestrial water storage is the sum of all forms of water storage on land surfaces, and its seasonal and interannual variations are in principle determined by soil moisture, groundwater, snow cover, and surface water. The dataset is derived with the combined atmospheric and terrestrial water-balance approach using conventional streamflow measurements and atmospheric moisture convergence data from the ECMWF 40-yr Re-Analysis (ERA-40). A recent study for the Mississippi River basin (Seneviratne et al. 2004) has demonstrated the validity of this diagnostic approach and found that it agreed well with in situ observations in Illinois. The present study extends this previous analysis to other regions of the midlatitudes. A systematic analysis is presented of the slow drift that occurs with the water-balance approach. It is shown ...

New data sets to estimate terrestrial water storage change

The total amount of water stored in a river basin affects streamflow at various timescales and defines the river basins response to atmospheric forcing. For example, spring runoff in mountainous midlatitude catchments depends on winter snowpack, and groundwater storage sustains flow during dry periods. An accurate estimation of terrestrial water storage (TWS) is thus paramount for improved water management. Direct determination of TWS is difficult due to insufficient in situ data on space-time variability of hydrologic stores (snow, soil moisture, groundwater) and fluxes (precipitation, evapotranspiration). However, alternative methods using new data sets show great potential to improve the estimation of intra-annual and interannual TWS dynamics.

Spatial representativeness of soil moisture using in situ, remote sensing, and land reanalysis data

This study investigates the spatial representativeness of the temporal dynamics of absolute soil moisture and its temporal anomalies over North America based on a range of data sets. We use three main data sources: in situ observations, the remote-sensing-based data set of the European Space Agency Climate Change Initiative on the Essential Climate Variable soil moisture (ECV-SM), and land surface model estimates from European Centre for Medium-Range Weather Forecastss ERA-Land. The intercomparisons of the three soil moisture data sources are performed at the in situ locations as well as for the full-gridded products. The applied method allows us to quantify the spatial footprint of soil moisture. At the in situ locations it is shown that for absolute soil moisture the ECV-SM and ERA-Land products perform similarly, while for the temporal anomalies the ECV-SM product shows more similarity in spatial representativeness with the in situ data. When taking into account all grid cells of the ECV-SM and ERA-Land products to calculate spatial representativeness, we find the largest differences in spatial representativeness for the absolute values. The differences in spatial representativeness between the single products can be related to some of their intrinsic characteristics, i.e., for ECV-SM low similarities are found in topographically complex terrain and areas with dense vegetation, while for ERA-Land the smoothed model topography and surface properties affect soil moisture and its spatial representativeness. Additionally, we show that the applied method is robust and can be used to analyze existing networks to provide insight into the locations in which higher station density would be of most benefit.

Quantifying Spatiotemporal Variations of Soil Moisture Control on Surface Energy Balance and Near-Surface Air Temperature

AbstractSoil moisture plays a crucial role for the energy partitioning at Earth’s surface. Changing fractions of latent and sensible heat fluxes caused by soil moisture variations can affect both near-surface air temperature and precipitation. In this study, a simple framework for the dependence of evaporative fraction (the ratio of latent heat flux over net radiation) on soil moisture is used to analyze spatial and temporal variations of land–atmosphere coupling and its effect on near-surface air temperature. Using three different data sources (two reanalysis datasets and one combination of different datasets), three key parameters for the relation between soil moisture and evaporative fraction are estimated: 1) the frequency of occurrence of different soil moisture regimes, 2) the sensitivity of evaporative fraction to soil moisture in the transitional soil moisture regime, and 3) the critical soil moisture value that separates soil moisture- and energy-limited evapotranspiration regimes. The results sh...

Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework

Richard Wartenburger1, Martin Hirschi1, Markus G. Donat2,3, Peter Greve4, Andy J. Pitman2,3, and Sonia I. Seneviratne1 1Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland 2ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, Australia 3Climate Change Research Centre, University of New South Wales, Sydney, Australia 4International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

Land radiative management as contributor to regional-scale climate adaptation and mitigation

Greenhouse gas emissions urgently need to be reduced. Even with a step up in mitigation, the goal of limiting global temperature rise to well below 2 °C remains challenging. Consequences of missing these goals are substantial, especially on regional scales. Because progress in the reduction of carbon dioxide emissions has been slow, climate engineering schemes are increasingly being discussed. But global schemes remain controversial and have important shortcomings. A reduction of global mean temperature through global-scale management of solar radiation could lead to strong regional disparities and affect rainfall patterns. On the other hand, active management of land radiative effects on a regional scale represents an alternative option of climate engineering that has been little discussed. Regional land radiative management could help to counteract warming, in particular hot extremes in densely populated and important agricultural regions. Regional land radiative management also raises some ethical issues, and its efficacy would be limited in time and space, depending on crop growing periods and constraints on agricultural management. But through its more regional focus and reliance on tested techniques, regional land radiative management avoids some of the main shortcomings associated with global radiation management. We argue that albedo-related climate benefits of land management should be considered more prominently when assessing regional-scale climate adaptation and mitigation as well as ecosystem services.Land management with the aim of reducing incoming solar radiation could help with regional-scale climate adaptation and mitigation as well as ecosystem services, and avoids several shortcomings of global geoengineering.

Global Contributions of Incoming Radiation and Land Surface Conditions to Maximum Near‐Surface Air Temperature Variability and Trend

Abstract The evolution of near‐surface air temperature is influenced by various dynamical, radiative, and surface‐atmosphere exchange processes whose contributions are still not completely quantified. Applying stepwise multiple linear regression to Coupled Model Intercomparison Project phase 5 (CMIP5) model simulations and focusing on radiation (diagnosed by incoming shortwave and incoming longwave radiation) and land surface conditions (diagnosed by soil moisture and albedo) about 79% of the interannual variability and 99% of the multidecadal trend of monthly mean daily maximum temperature over land can be explained. The linear model captures well the temperature variability in middle‐to‐high latitudes and in regions close to the equator, whereas its explanatory potential is limited in deserts. While radiation is an essential explanatory variable over almost all of the analyzed domain, land surface conditions show a pronounced relation to temperature in some confined regions. These findings highlight that considering local‐to‐regional processes is crucial for correctly assessing interannual temperature variability and future temperature trends.

Variability of Soil Moisture Proxies and Hot Days Across the Climate Regimes of Australia

The frequency of extreme events such as heatwaves are expected to increase due to the effect of climate change, particularly in semi-arid regions areas of Australia. Recent studies have indicated a link between soil moisture deficits and heat extreme, focusing on the coupling between the two. This study investigates the relationship between the number of hot-days (Tx90) and four soil moisture proxies (SPI, API, MSDI and KBDI), and how the strength of this relationship changes across various climate regimes within Australia. A strong anti-correlation between Tx90 and each moisture index is found, particularly for tropical savannas and temperate regions. However, the magnitude of the increase in Tx90 with decreasing moisture is strongest in semi-arid and arid regions. It is also shown that the Tx90-soil moisture relationship strengthens during the El Nino phases of ENSO in regions which are more sensitive to changes in soil moisture.