Data assimilation in a sparsely observed one-dimensional modeled MHD system

A one dimensional non-linear magneto-hydrodynamic (MHD) system has been introduced to test a sequential optimal interpolation assimilation technique that uses a Monte-Carlo method to calculate the forecast error covariance. An ensemble of 100 model runs with perturbed initial conditions are used to construct the covariance, and the assimilation algorithm is tested using Observation Simulation Experiments (OSE's). The system is run with a variety of observation types (magnetic and/or velocity fields) and a range of observation densities. The impact of cross covariances between velocity and magnetic fields is investigated by running the assimilation with and without these terms. Sets of twin experiments show that while observing both velocity and magnetic fields has the greatest positive impact on the system, observing the magnetic field alone can also effectively constrain the system. Observations of the velocity field are ineffective as a constraint on the magnetic field, even when observations are made at every point. The implications for geomagnetic data assimilation are discussed

Data assimilation in a sparsely observed one-dimensional modeled MHD system

International audienceA one dimensional non-linear magneto-hydrodynamic (MHD) system has been introduced to test a sequential optimal interpolation assimilation technique that uses a Monte-Carlo method to calculate the forecast error covariance. An ensemble of 100 model runs with perturbed initial conditions are used to construct the covariance, and the assimilation algorithm is tested using Observation Simulation Experiments (OSE's). The system is run with a variety of observation types (magnetic and/or velocity fields) and a range of observation densities. The impact of cross covariances between velocity and magnetic fields is investigated by running the assimilation with and without these terms. Sets of twin experiments show that while observing both velocity and magnetic fields has the greatest positive impact on the system, observing the magnetic field alone can also effectively constrain the system. Observations of the velocity field are ineffective as a constraint on the magnetic field, even when observations are made at every point. The implications for geomagnetic data assimilation are discussed

Improving estimation of glacier volume change: a GLIMS case study of Bering Glacier System, Alaska

International audienceThe Global Land Ice Measurements from Space (GLIMS) project has developed tools and methods that can be employed by analysts to create accurate glacier outlines and resultant measures of glacier extent. To illustrate the importance of accurate glacier outlines and the effectiveness of GLIMS standards we have conducted a case study on Bering Glacier System (BGS), Alaska. BGS is a complex glacier system aggregated from multiple drainage basins, numerous individual ice streams, and many accumulation areas. Published measurements of BGS surface area vary from 1740 to 6200 km2, depending on how the boundaries of this system have been defined. Utilizing GLIMS tools and standards we have completed a new outline and analysis of the area-altitude distribution (hypsometry) of BGS using Landsat images from 2000 and 2001. We compared this new outline (3632 km2) with three previous outlines to illustrate the errors that result from the widely varying estimates used in previous analysis of BGS area. The use of different BGS outlines results in highly variable measures of volume change and net balance (bn). Outline variability alone results in a net balance rate range of ?1.0 to ?3.2 m/yr water equivalent (W.E.), a volume change range of ?4.2 to ?8.2 km3/yr, and a near doubling in contributions to sea level equivalent (SLE), 0.0122 mm/yr to 0.0236 mm/yr. A study of three different models of BGS net balance leads us to favor estimates of bn of ?1.2 m/yr W.E. and total volume change of ?4.2 km3/yr for the period 1950?2004. These estimates result in a near doubling of contributions to sea level equivalent when compared with previous studies. While current inaccuracies in glacier outlines hinder our ability to fully understand glacier change, there is no reason why our understanding of glacier extents should not be comprehensive and accurate. Such accuracy is possible with the increasing volume of satellite imagery of glacierized regions, and recent advances in tools and standards

Debris cover and surface melt at a temperate maritime alpine glacier: Franz Josef Glacier, New Zealand

Melt rates on glaciers are strongly influenced by the presence of supraglacial debris, which can either enhance or reduce ablation relative to bare ice. Most recently, Franz Josef Glacier has entered into a phase of strong retreat and downwasting, with the increasing emergence of debris on the surface in the ablation zone. Previously at Franz Josef Glacier, melt has only been measured on bare ice. During February 2012, a network of 11 ablation stakes was drilled into locations of varying supraglacial debris thickness on the lower glacier. Mean ablation rates over 9 days varied over the range 1.2–10.1 cm d−1, and were closely related to debris thickness. Concomitant observations of air temperature allowed the application of a degree-day approach to the calculation of melt rates, with air temperature providing a strong indicator of melt. Degree-day factors (d f) varied over the range 1.1–8.1 mm d−1 °C−1 (mean of 4.4 mm d−1 °C−1), comparable with rates reported in other studies. Mapping of the current debris cover revealed 0.7 km2 of the 4.9 km2 ablation zone surface was debris-covered, with thicknesses ranging 1–50 cm. Based on measured debris thicknesses and d f, ablation on debris-covered areas of the glacier is reduced by a total of 41% which equates to a 6% reduction in melt overall across the entire ablation zone. This study highlights the usefulness of a short-term survey to gather representative ablation data, consistent with numerous overseas ablation studies on debris-covered glaciers

International Geomagnetic Reference Field: the eleventh generation

The eleventh generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2009 by the International Association of Geomagnetism and Aeronomy Working Group V-MOD. It updates the previous IGRF generation with a definitive main field model for epoch 2005.0, a main field model for epoch 2010.0, and a linear predictive secular variation model for 2010.0-2015.0. In this note the equations defining the IGRF model are provided along with the spherical harmonic coefficients for the eleventh generation. Maps of the magnetic declination, inclination and total intensity for epoch 2010.0 and their predicted rates of change for 2010.0-2015.0 are presented. The recent evolution of the South Atlantic Anomaly and magnetic pole positions are also examine

International Geomagnetic Reference Field: the eleventh generation

The eleventh generation of the International Geomagnetic Reference Field (IGRF)was adopted in December 2009 by the International Association of Geomagnetism and AeronomyWorking Group V-MOD. It updates the previous IGRF generation with a definitive main field model for epoch 2005.0, a main field model for epoch 2010.0, and a linear predictive secular variation model for 2010.0–2015.0. In this note the equations defining the IGRF model are provided along with the spherical harmonic coefficients for the eleventh generation. Maps of the magnetic declination, inclination and total intensity for epoch 2010.0 and their predicted rates of change for 2010.0–2015.0 are presented. The recent evolution of the South Atlantic Anomaly and magnetic pole positions are also examined

International Geomagnetic Reference Field: the thirteenth generation

In December 2019, the International Association of Geomagnetism and Aeronomy (IAGA) Division V Working Group (V-MOD) adopted the thirteenth generation of the International Geomagnetic Reference Field (IGRF). This IGRF updates the previous generation with a definitive main field model for epoch 2015.0, a main field model for epoch 2020.0, and a predictive linear secular variation for 2020.0 to 2025.0. This letter provides the equations defining the IGRF, the spherical harmonic coefficients for this thirteenth generation model, maps of magnetic declination, inclination and total field intensity for the epoch 2020.0, and maps of their predicted rate of change for the 2020.0 to 2025.0 time period

Single-footprint retrievals for AIRS using a fast TwoSlab cloud-representation model and the SARTA all-sky infrared radiative transfer algorithm

One-dimensional variational retrievals of temperature and moisture fields from hyperspectral infrared (IR) satellite sounders use cloud-cleared radiances (CCRs) as their observation. These derived observations allow the use of clear-sky-only radiative transfer in the inversion for geophysical variables but at reduced spatial resolution compared to the native sounder observations. Cloud clearing can introduce various errors, although scenes with large errors can be identified and ignored. Information content studies show that, when using multilayer cloud liquid and ice profiles in infrared hyperspectral radiative transfer codes, there are typically only 2–4 degrees of freedom (DOFs) of cloud signal. This implies a simplified cloud representation is sufficient for some applications which need accurate radiative transfer. Here we describe a single-footprint retrieval approach for clear and cloudy conditions, which uses the thermodynamic and cloud fields from numerical weather prediction (NWP) models as a first guess, together with a simple cloud-representation model coupled to a fast scattering radiative transfer algorithm (RTA). The NWP model thermodynamic and cloud profiles are first co-located to the observations, after which the N-level cloud profiles are converted to two slab clouds (TwoSlab; typically one for ice and one for water clouds). From these, one run of our fast cloud-representation model allows an improvement of the a priori cloud state by comparing the observed and model-simulated radiances in the thermal window channels. The retrieval yield is over 90 %, while the degrees of freedom correlate with the observed window channel brightness temperature (BT) which itself depends on the cloud optical depth. The cloud-representation and scattering package is benchmarked against radiances computed using a maximum random overlap (RMO) cloud scheme. All-sky infrared radiances measured by NASA's Atmospheric Infrared Sounder (AIRS) and NWP thermodynamic and cloud profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model are used in this paper