On requirements for a satellite mission to measure tropical rainfall

Tropical rainfall data are crucial in determining the role of tropical latent heating in driving the circulation of the global atmosphere. Also, the data are particularly important for testing the realism of climate models, and their ability to simulate and predict climate accurately on the seasonal time scale. Other scientific issues such as the effects of El Nino on climate could be addressed with a reliable, extended time series of tropical rainfall observations. A passive microwave sensor is planned to provide information on the integrated column precipitation content, its areal distribution, and its intensity. An active microwave sensor (radar) will define the layer depth of the precipitation and provide information about the intensity of rain reaching the surface, the key to determining the latent heat input to the atmosphere. A visible/infrared sensor will provide very high resolution information on cloud coverage, type, and top temperatures and also serve as the link between these data and the long and virtually continuous coverage by the geosynchronous meteorological satellites. The unique combination of sensor wavelengths, coverages, and resolving capabilities together with the low-altitude, non-Sun synchronous orbit provide a sampling capability that should yield monthly precipitation amounts to a reasonable accuracy over a 500- by 500-km grid

Modelling and observing urban climate in the Netherlands

Volgens de klimaatscenario’s van het KNMI uit 2006 zal de gemiddelde temperatuur in Nederland in de komende decennia verder stijgen. Hittegolven zullen naar verwachting vaker voorkomen en de intensiteit van met name zomerse buien kan toenemen. In steden zijn de gevolgen van de opwarming extra voelbaar, omdat de temperaturen er door het zogenoemde Urban Heat Island (UHI) effect veel hoger kunnen zijn dan in het omliggende gebied. Zulke periodes met hoge temperaturen gaan veelal gepaard met verslechterde luchtkwaliteit en droogte. Dit alles kan grote gevolgen hebben voor de leefbaarheid en de gezondheid van de bevolking in stedelijke gebieden. Veranderingen in de buienintensiteit beïnvloeden de waterhuishouding van de stad

In-situ measurements of oxygen, carbon monoxide and greenhouse gases from Ochsenkopf tall tower in Germany

We present 2.5 years (from June 2006 to December 2008) of in-situ measurements of CO2, O2, CH4, CO, N2O and SF6 mixing ratios sampled from 23, 90 and 163m above ground on the Ochsenkopf tower in the Fichtelgebirge range, Germany (50?0104900 N, 11?4803000 E, 1022ma.s.l.). In addition to the in-situ measurements, flask samples are taken at Ochsenkopf at approximately weekly intervals and are subsequently analysed for the mixing ratios of the same species, as well as H2, and the stable isotopes, ?13C, ?18O in CO2. The in-situ measurements of CO2 and O2 from 23m show substantial diurnal variations that are modulated by biospheric fluxes, combustion of fossil fuels, and by diurnal changes in the planetary boundary layer height. Measurements from 163m exhibit only very weak diurnal variability, as this height (1185ma.s.l.) is generally above the nocturnal boundary layer. CH4, CO, N2O and SF6 show little diurnal variation even at 23m owing to the absence of any significant diurnal change in the fluxes and the absence of any strong local sources or sinks. From the in-situ record, the seasonal cycles of the gas species have been characterized and the multi-annual trends determined. Because the record is short, the calculation of the trend is sensitive to inter-annual variations in the amplitudes of the seasonal cycles. However, for CH4 a significant change in the growth-rate was detected for 2006.5–2008.5 as compared with the global mean from 1999 to 2006 and is consistent with other recent observations of a renewed increasing global growth rate in CH4 since the beginning of 2007

Sensitivity analysis and calibration of multi energy balance land surface model parameters

Flows of energy between the atmosphere, the oceans and the land surfaces drive weather and climate on Earth. Increased understanding of these processes is crucial to successfully predict and address the challenges of climate change. Land surface models (LSM) are mathematical models designed to mimic natural processes and evolution of land surfaces with the basic task to simulate surface-atmosphere energy flows. Within the SURFace EXternalisée modeling platform (SURFEX), developed by Météo-France and a suite of international partners, a new LSM called the Interaction Soil Biosphere Atmosphere model - Multi Energy Balance (ISBA-MEB) has been developed. There are however still uncertainties in how to accurately prescribe model parameters used to numerically define the physiography and natural processes of modelled land surfaces which consequently results in uncertainties in modelled outputs. In the present study, Quasi-Monte Carlo simulations based on Sobol sensitivity analysis was applied to explore the uncertainty contribution of individual parameters to modelled surface-atmosphere turbulent sensible and latent heat fluxes in forest environments. Those parameters to which modelled fluxes were identified as significantly sensitive were then calibrated by generating multiple sets of parameter values with the Latin Hypercube sampling technique on which the model was run to identify what parameter values generated the least amount of model output bias and to evaluate how much model output uncertainty could be reduced. To explore variations in parameter sensitivity and optimal parameter prescriptions between forest environments, four separate forest areas with varying vegetation types and climate classifications were modelled. Results disclose that the level of uncertainty contribution of individual parameters varies between forest environments. Three parameters were however identified to contribute with significantly output uncertainty; 1) the ration between roughness length of momentum and thermal roughness length, 2) the heat capacity of vegetation and soil and 3) the leaf orientation at canopy bottom. Calibrating these parameters marginally reduced model output uncertainty at all study areas.Jorden tar emot ett konstant flöde av energi via solinstrålning som sedan cirkulerar mellan atmosfären, haven och markytan innan den slutligen strålas ut i rymden. Dessa energiflöden är bränslet som driver planetens väder- och klimatfenomen och det vetenskapliga samfundet efterfrågar ökad kunskap om detta system för att utmaningarna med klimatförändringar ska kunna förutspås och hanteras. En grundläggande komponent i klimatsystemet är markytans energiutbyte med atmosfären. Hur stora dessa energiflöden är och i vilken form som energin transporteras avgörs av väderförhållanden och markens fysiska egenskaper. Inom exempelvis meteorologi och hydrologi simuleras dessa processer med hjälp av Markytamodeller. I ett internationellt samarbete med utgångspunkt i Frankrikes meteorologiska institut Météo France har en ny Markytamodell för simulering av naturmiljöer utvecklats. Denna modell möjliggör en mer detaljerad beskrivning av markytans fysiska komponenter, så som karaktären på jord och vegetation, än sina förgångare. Markytamodeller är matematiska och lanskapets karaktär beskrivs därför numeriska parametrar. I nuläget råder det osäkerhet kring hur vissa av dessa parametrar bäst definieras i olika skogstyper. Eftersom markytans olika fysiska komponenter har olika inflytande på energiflöden har även Markytamodellers parmetrar olika inflytande på simuleringen av dessa energiflöden. Detta uttrycks även som att modellen är olika känslig för olika parametrar. Syftet med denna studie var att undersöka hur känslig den nya Markmodellen är för olika vegetationsparametrar i olika skogsmiljöer. Vidare var syftet att undersöka hur mycket simuleringar kan förbättras genom att finna det optimala värdet på de mest känsliga parametrarna i respektive skogsområde. Skillnader i parameterkänslighet och optimala parametervärden för fyra olika skogsmiljöer identifierades med så kallade Monte-Carlo simuleringar. Kortfattat innebar detta att skogsmiljöerna modellerades upprepade gånger med olika parametervärden. Slutsatserna är att parameterkänsligheten varierar mellan de inkluderade skogsområdena, men att modellen är mycket känsliga för tre av de analyserade parametrarna. Genom att identifiera optimala värden för dessa mycket känsliga parametrar i respektive skogsmiljö kunde mer realistiska simuleringar av energiflöden uppnås

CLAUS Final Report

Cloud archive user service (CLAUS

Optimal estimation of sea surface temperature from AMSR-E

The Optimal Estimation (OE) technique is developed within the European Space Agency Climate Change Initiative (ESA-CCI) to retrieve subskin Sea Surface Temperature (SST) from AQUA’s Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E). A comprehensive matchup database with drifting buoy observations is used to develop and test the OE setup. It is shown that it is essential to update the first guess atmospheric and oceanic state variables and to perform several iterations to reach an optimal retrieval. The optimal number of iterations is typically three to four in the current setup. In addition, updating the forward model, using a multivariate regression model is shown to improve the capability of the forward model to reproduce the observations. The average sensitivity of the OE retrieval is 0.5 and shows a latitudinal dependency with smaller sensitivity for cold waters and larger sensitivity for warmer waters. The OE SSTs are evaluated against drifting buoy measurements during 2010. The results show an average difference of 0.02 K with a standard deviation of 0.47 K when considering the 64% matchups, where the simulated and observed brightness temperatures are most consistent. The corresponding mean uncertainty is estimated to 0.48 K including the in situ and sampling uncertainties. An independent validation against Argo observations from 2009 to 2011 shows an average difference of 0.01 K, a standard deviation of 0.50 K and a mean uncertainty of 0.47 K, when considering the best 62% of retrievals. The satellite versus in situ discrepancies are highest in the dynamic oceanic regions due to the large satellite footprint size and the associated sampling effects. Uncertainty estimates are available for all retrievals and have been validated to be accurate. They can thus be used to obtain very good retrieval results. In general, the results from the OE retrieval are very encouraging and demonstrate that passive microwave observations provide a valuable alternative to infrared satellite observations for retrieving SST

Observational needs of sea surface temperature

Sea surface temperature (SST) is a fundamental physical variable for understanding, quantifying and predicting complex interactions between the ocean and the atmosphere. Such processes determine how heat from the sun is redistributed across the global oceans, directly impacting large- and small-scale weather and climate patterns. The provision of daily maps of global SST for operational systems, climate modeling and the broader scientific community is now a mature and sustained service coordinated by the Group for High Resolution Sea Surface Temperature (GHRSST) and the CEOS SST Virtual Constellation (CEOS SST-VC). Data streams are shared, indexed, processed, quality controlled, analyzed, and documented within a Regional/Global Task Sharing (R/GTS) framework, which is implemented internationally in a distributed manner. Products rely on a combination of low-Earth orbit infrared and microwave satellite imagery, geostationary orbit infrared satellite imagery, and in situ data from moored and drifting buoys, Argo floats, and a suite of independent, fully characterized and traceable in situ measurements for product validation (Fiducial Reference Measurements, FRM). Research and development continues to tackle problems such as instrument calibration, algorithm development, diurnal variability, derivation of high-quality skin and depth temperatures, and areas of specific interest such as the high latitudes and coastal areas. In this white paper, we review progress versus the challenges we set out 10 years ago in a previous paper, highlight remaining and new research and development challenges for the next 10 years (such as the need for sustained continuity of passive microwave SST using a 6.9 GHz channel), and conclude with needs to achieve an integrated global high-resolution SST observing system, with focus on satellite observations exploited in conjunction with in situ SSTs. The paper directly relates to the theme of Data Information Systems and also contributes to Ocean Observing Governance and Ocean Technology and Networks within the OceanObs2019 objectives. Applications of SST contribute to all the seven societal benefits, covering Discovery; Ecosystem Health & Biodiversity; Climate Variability & Change; Water, Food, & Energy Security; Pollution & Human Health; Hazards and Maritime Safety; and the Blue Economy

Reducing bias on soil surface CO2 flux emission measurements : Case study on a mature oil palm (Elaeis guineensis) plantation on tropical peatland in Southeast Asia

We are highly grateful to Ham Jonathon, and Steward Saging for their help and in the field work, setup of the experiments, assisting with data collection and most importantly permission to utilize the dataset.Peer reviewe

The role of water vapor in climate. A strategic research plan for the proposed GEWEX water vapor project (GVaP)

The proposed GEWEX Water Vapor Project (GVaP) addresses fundamental deficiencies in the present understanding of moist atmospheric processes and the role of water vapor in the global hydrologic cycle and climate. Inadequate knowledge of the distribution of atmospheric water vapor and its transport is a major impediment to progress in achieving a fuller understanding of various hydrologic processes and a capability for reliable assessment of potential climatic change on global and regional scales. GVap will promote significant improvements in knowledge of atmospheric water vapor and moist processes as well as in present capabilities to model these processes on global and regional scales. GVaP complements a number of ongoing and planned programs focused on various aspects of the hydrologic cycle. The goal of GVaP is to improve understanding of the role of water vapor in meteorological, hydrological, and climatological processes through improved knowledge of water vapor and its variability on all scales. A detailed description of the GVaP is presented