1. Julia Stoyanova, Christo Georgiev, Plamen Neytchev
Using land surface analyses to assess weather extremes: Heat waves and drought effects
National Institute of Meteorology and Hydrology
Bulgarian Academy of Sciences
5th SALGEE Workshop, September, Yerevan, Armenia
‘MSG Land Surface Applications: Heat waves, Drought Hazard and Fire Monitoring’ 1

2. Using land surface analyses to assess weather extremes: Heat waves and drought effects
Outline
1.  Spectrum of weather extremes and terrestrial drought
2. Role of land-atmosphere coupling to produce high impact weather: Heat Waves (HW) and land surface state
Key parameters and meteorological processes
Principles and practices of land surface analyses
3.  Meteosat in support to diagnoses and forecast of ‘dry’ land surface anomalies
4. Quantification of HW-drought effects with some focus on the role of soil moisture: Case study examples 2 2

3. 1. Spectrum of weather extremes and terrestrial drought
Climate model simulations project that this trend will continue in the future and that extremely hot summers will become more frequent, more intense and longer lasting.
1. Spectrum of weather extremes and terrestrial drought
Forest/wild fires
positive temperature
anomaly
Transport/
energy sector
Drought
related weather
Socioeconomic
activities
effects on
water bodies
lack of precipitation and
enhanced evaporation
reduction in the
productivity of
natural and cultivated
vegetation
other effects
In theory, a weather-type could be high-impact by virtue of it being inherently less predictable – so society does not have sufficient forewarning to take mitigating action – although many of the relevant weather features will be extreme in amplitude anyway, for example droughts. 3

4. Drought identification
Spectrum of drought
Drought does not belong to the group of climate extremes based on simple climate statistics, as anomalies in daily temperature or heavy rainfall amount that occur every year. Drought is a more complex event-driven extreme, which do not necessarily occur every year at a given location.
usually defined as a significant negative
deviation from mean precipitation
Meteorological drought
a deficit in the supply of surface and sub-
surface water (run-off, water levels)
Hydrological drought
hydrological droughts resulting in reduced
a combination of meteorological and
supply of moisture levels for crops)
Agricultural drought
reflected by ecosystem functioning
Ecological drought
combination of the above droughts leading
to undesirable social and economic impacts
Socioeconomic drought
Drought is part of the natural climate variability and therefore can be observed in all climate regimes. Unlike aridity, drought is a temporary abnormal phenomenon, usually characterized by lower than average water availability for the population or for the environment. There is no unique or universally accepted definition of drought.

5. Drought imposes prolonged HIW regime
Projected increase in temperature variability is strongly related to changes in Soil Moisture (SM) and in particular to changes in the strength of SM‐atmosphere coupling.
Spectrum of High Impact Weather (HIW) events
HIW is weather that can result in significant impacts on safety, property and/or socioeconomic activity (Sills 2009).
extreme in amplitude
prolonged ‘regimes’
rapid cyclogenesis, intense winds, heavy convective precipitation, wind gusts
droughts, heat-waves or cold-spells
Drought imposes prolonged HIW regime
These features are a challenge to define, let-alone predict, because they represent the aggregate of interactions between planetary waves (possibly remotely-forced, smaller spatio-temporal scale variability) including land – atmosphere coupling.
Sills, D. M. L. (2009) On the msc forecasters forums and the future role of the human forecaster, B. Am. Meteorol. Soc., 90, 619,doi: /2008BAMS2657.1, 5

6. HW related physical mechanisms
Land-atmosphere coupling is a driving mechanism underlying European summer heat waves (HW)
Three large-scale Physical mechanisms have been identified as fundamental factors in producing summer HWs in Europe:
persistent anticyclonic circulation anomalies (i.e. atmospheric stability)
sea surface temperatures (SSTs) anomalies in the North Atlantic, Mediterranean and/or Indian Ocean
anomalous land surface conditions (e.g. drought) (Stéfanon, 2012).
Land-atmosphere coupling of several elements - such as atmospheric stability, sea surface temperature anomaly and drought - led to the very exceptional 2003 heat waves with a temperature up by 12.5 °C with respect to climatological observations realised between (Levinson and Waple, 2004).
Stéfanon, M. (2012) Heat waves and droughts in Mediterranean: contributions of land-atmosphere coupled processes on mesoscale. THÈSE pour l’obtention du grade de Docteur de l’École polytechnique, spécialité : Physique, Laboratoire de Météorologie DynamiqueInstitut Pierre Simon Laplace, 123 p.
Levinson,D.H. and A.M.Waple (2004) State of the climate in Bull. Amer. Meteorol. Soc., 85, S1 S72.

7. Risk effects on Ecosystems and Environment
Summer dryness in Mediterranean during Heat Waves has different manifestations:
agricultural drought (soil moisture deficits)
fire weather/fire risk
declined Net Primary Productivity of forests, etc.
Triggered by large-scale atmospheric forcings, Mediterranean regional heat waves are often amplifed by surface preconditioning, such as negative soil moisture anomalies and vegetation state (Stéfanon et al, 2013).
Terrestrial drought Wild/forest fires Declined productivity
Stéfanon, M., P. Drobinski, F.D’Andrea, C.Lebeaupin-Brossier, S.Bastin (2013) Soil moisture-temperature feedbacks at meso-scale during summer heat waves over Western Europe. Clim Dyn, DOI /s 7

8. “hot spots’’ of land- atmosphere coupling
In SM‐limited regions, the partitioning of the surface energy into sensible (H) and latent heat (LE) fluxes is strongly determined by SM.
“hot spots’’ of land- atmosphere coupling
Regions where SM most impacts the atmosphere are transitional zones between dry and wet climates (Koster et al., 2004).
 For present climate: also the southern Europe/ Mediterranean region have been identified as such regions (Zhang et al., 2008).
These “hot spots” of land–atmosphere coupling is expected to be modified with shifts in climate regimes for instance due to climate change.
Koster R.D., et al. (2004) Regions of strong coupling between soil moisture and precipitation. Science, 305,
Zhang, J., W.-C. Wang, Wei, J. (2008) Assessing land-atmosphere coupling using soil moisturefrom the Global Land Data Assimilation System and observational precipitation. J. Geophys. Res., 113, D17119, doi: /2008JD0098.

9. 2. Land-atmosphere coupling
Key parameters and meteorological processes
Land-Atmosphere coupling is based on ecosystems functioning, which are at the bottom of atmosphere
Coupling of energy-water cycles is the bases of ecosystems functioning that is resulting in transformation of solar energy into the energetic fluxes of latent heat, LE and sensible heat, H towards atmosphere, and in the soil, G.
wet climate regime
dry climate regime
Seneviratne et al. (2011)
Natural and anthropogenic systems such as forests and crops have different behavior under heat waves conditions (Teuling et al. (2010). Contrasting response of European forest and grassland energy exchange to heat waves. Nature Geoscience 3,722–727, doi: /ngeo950).
The changes in soil moisture have the larger impact on the surface climate on timescales ranging of days to seasons.

10. Key parameters and meteorological processes
The role of soil moisture in propagation of Mediterranean drought: Coupling of energy-water cycles at ‘Dry’- ‘Wet’ soil is reflected by the proportion between LE and H.
A better description, understanding and modelling of soil moisture and associated land- atmosphere interaction would improve the predictability at both daily and sub seasonal scale.
Land Surface Temperature (LST) is a Key Parameter in the distribution of the energetic fluxes at a specific land cover.
wet climate regime
dry climate regime
Seneviratne et al. (2011)
LST derived by satellite data can be a valuable source of information to adequately respond to the demands of environmental monitoring and drought risk management. 10

11. 2. Land-atmosphere coupling
Land surface state analysis: Basic methods & principles
Land Surface Modeling, LSMs
Satellite observations
dry wet
Difficulties: LS heterogeneity
Parameterization of land-surface processes in NWP
Tskin
Retrievals
5 cm
20 cm
50 cm
100 cm
Root zone depth
Source: Gianpaolo Balsamo 11

12. 2. Land-atmosphere coupling
Parameterization of soil moisture, vegetation cover
SMA is a measure of both: SM dynamics and vegetation functioning, which in turn is reflected by LS state indicators: Ts, LE, H, E, etc.
Meteorological models govern parameterization of these energetic processes.
dry wet
Limited soil
moisture availability
At limiting SM conditions, the evapotranspiration from the plant community is restricted and controlled by soil.
At non-limiting SM conditions evapotranspiration is controlled by meteorological variables.
Optimum of soil
Soil Moisture (SM) available to plants is an important variable for evaluating vegetation transpiration; a key factor
in models of ecosystem and carbon cycle processes; energy and water budgets of crop canopies, as well as
a basic parameter in mesoscale atmospheric circulation models and forecasting systems. 12

13. Limitations & Advantages of LSA SAF MSG products use for LSA
3. Meteosat in support to diagnoses and forecast of ‘dry’ land surface anomalies
Remote sensing provides the best means to monitor changes in vegetation cover in a wide range of temporal scales over large areas
A number of MSG based LSA SAF products provide useful information for characterizing land surface state in cases of HIW and fires in the region of southeastern part of Europe.
Given the high impact of drought and wild/forest fires on society, the implications of satellite information for the management and control of these phenomena by characterizing land surface conditions and issuing early warnings is an important operational task.
Limitations & Advantages of LSA SAF MSG products use for LSA
Highest time frequency, especially valuable for fire detection, but lower spatial resolution of MSG.
Cloudiness is a severe limitation factor.
Microwave sounders are alternative solution (for LST, Soil moisture retrievals).
For correct interpretation of vegetation state from satellite data, Land Surface Models and NWP models are needed.

14. 4.  Quantification of HW-drought effects with some focus on the role of soil moisture
Characteristics of Eastern Mediterranean heat waves  drought relations:
Soil Moisture (SM) deficit, characterized by Soil Moisture Availability (SMA) to vegetation cover
Land surface temperature (LST)
Temperature difference between land surface and atmosphere (2m height).
Climatic data set: March-October heat wave episodes.
Local reveals of large-scale processes : Bulgaria,
southeastern Europe
The aim: In this work we evaluate the land surface state during heat waves by using biogeophysical moistening- and thermal- parameters, and perform a short climatic survey, both aimed specifically to:
evaluate the relations between SM and termal parameter of land-atmosphere system during HWs
define the potential influence of SM deficit to the HW intensity during days/seasons.
to test the utility of Meteosat based LSA SAF LST/(LST-T2m) as a proxy of SM during HWs.

15. Data set for assessment / monitoring of heat wave-drought effects
Only periods with HWs are considered
Data set for assessment / monitoring of heat wave-drought effects
Biogeophysical parameters (from models and Meteosat)
Soil Moisture (SM)
 SM at 3 depths along the soil profile (20, 50, 100 cm)
 ‘SVAT_bg’ model output of SM, accounting for regional climate, soil type/properties
Soil moisture deficit (agricultural drought)
 Soil Moisture Availability Index (SMAI) (Stoyanova & Georgiev, 2013)
 6-level threshold scheme for SMA quantitative assessment
Land Surface Temperature, Ts
 LSA SAF LST product, 09:00  30 min UTC (12:00 LT)
 MSG LSA SAF LST averaged values of 3x3 pixels around the SYNOP locations
Vegetation water stress: Temperature difference between LSA SAF LST and air temperature at 2 m height (T2m), (LST–T2m)
Air temperature: observations (SYNOP network of Bulgaria)
 T2m at 09:00 UTC
Climatic data set:
 March-October
Stoyanova, J.S. and Georgiev, C.G. (2013) SVAT modelling in support to flood risk assessment in Bulgaria. Atmos. Res., 123,

16. Heat Wave /HW/ denition used
Extreme events are easy to recognize but difficult to define, as the concept of “extremeness” is strongly dependent on Context
Heat Wave /HW/ denition used
We adopt a relative definition of
heat waves.
To define a hot day, time (day) dependent thresholds of the 95th percent quantile of local daily maximum temperature (Tmax) using a long-term base period .
HWs are defined as prolonged periods of extreme heat with Tmax exceeding the day 95 %qn threshold and lasting at least three consecutive days.
At this initial stage of HW study, Tmax exceeding corresponding 95% quantile even for 1 day is used for some of surveys.

17. A. Land-atmosphere temperature conditions during HWs
Analyses and diagnoses of land surface state during HWs in E-Mediterranean
June
Fig. 1. Temperature environment during 95 %qn HW episodes: Example for north Bulgaria: March, May, July, August 2007.
0900 UTC LST increases C (March) up to 48.6 C (July) 2007
T2m vary between C (March) up to 38.3 C (July), about 10 C lower than LST
Tmax higher from 22.9 C (March) – 44.5 C (July), about 4 C higher than T2m
2007 is characterized with high temperatures and records, enhanced fire risk, a peak of fire activity, being the second in ranking (after 2000) the number of observed forest fires (by State Forest Agency of Bulgaria); in July forest fires are maximal (530) not only for but for the whole period of their archiving in a National Data Base (since 2000).

18. B. Land surface moistening during HWs During HWs SMA becomes negative.
Analyses and diagnoses of land surface state during HWs in E-Mediterranean
March
May
June
July
Aug
Fig. 2. Soil moistening characterized by SMA during 95 %qn HW episodes of 2007 along with temperature environment. Example from Fig.1.
Steadily depletion of SMA along with increasing LST, Tmax, T2m.
Terrestrial drought: SMA 20 cm becomes negative still at 22 June, 3 days later after it becomes negative for 50 cm; at 100 cm depths, SMA is exhausted at 10 July. Strong SMD until the end of HW episodes in 2007.
SMA to vegetation cover is used as a quantitative measure of soil moisture deficit.
During HWs SMA becomes negative.

19. C. Physical relations between HWs and drought
Analyses and diagnoses of land surface state during HWs in E-Mediterranean
March
May
June
July
Aug
As a result, high Ts is both a cause and the consequence of dry periods.
The SM decrease (in conditions of meteorological drought) leads to SMA depletion and reduced evaporative cooling of the land surface, which is accompanied by steadily increase of LST.
Changes in soil moisture affect the albedo and thermal diffusivity of the soil and the Bowen ratio (the ratio of the sensible to latent heat fluxes) in the atmospheric surface boundary layer.
As a moist soil surface dries out, more of the incoming solar energy is reflected, and a larger fraction of the absorbed energy is used to heat the air and soil. The heat flow into the soil increases at first, then decreases as the soil becomes very dry. This results in higher land surface temperatures, which also influence the rate of drying and evapotranspiration.

20. D. Soil moisture feedback on temperature
Soil Moisture Control on Land Surface Fluxes
The evolution of LS – Atmosphere environment is governed by biophysical processes
The suggested physical mechanism linking soil moisture and HWs is a positive feedback whereby dry soils intensify upper level anticyclonic anomalies due to higher sensible heat flux, which in turn leads to higher temperatures at the surface (Fischer et al. 2007).

21. D. Soil moisture feedback on temperature during HWs
Soil Moisture Control on Land Surface Fluxes
During HWs, the dry soil (in the coupled simulations) favors H increase (at the expense of latent LE), which in turn enhances the Ts.
At negative SMA, H is the dominant energetic flux,
Precipitations can restore positive SMA, than LE can become dominant.
The suggested physical mechanism linking soil moisture and HWs is a positive feedback whereby dry soils intensify upper level anticyclonic anomalies due to higher sensible heat flux, which in turn leads to higher temperatures at the surface (Fischer et al. 2007).

22. E. Land surface  Air temperature difference
Analyses and diagnoses of land surface state during HWs in E-Mediterranean
March
May
June
July
Aug
The quantification of land surface state is performed via the blended parameter 0900 UTC (LSA SAF LST-T2m) (magenta) during HW episodes in spring (March, May), in summer (June, July, August) of 2007
The skin-air temperature difference during periods of HWs has a definite course depending on: season (e.g. land cover developed), SMA and its depletion along the root zone depth.

23. E. Land surface  Air temperature difference variations during HWs
2007
2007
May
July
positive SMA
June
negative SMA
Trends in (LST-T2m) difference values exhibit:
In spring when the LC is not fully developed, although high positive SMA, (LST-T2m) is high (12-13 C).
At full LC and positive SMA it starts to decrease (June, 3.6 – 7 C).
Along with SMA depletion (July), it starts to increase up to 14 C.
During drought (SMA negative), it varies around close high values (12-14 C).
March
May
July
Aug
The (Ts-T2m) temperature difference during HWs may serve as a measure of SMA, respectively of drought occurrence on a daily basis.

24. F. Seasonal course of temperature difference (LSA SAF LST-T2m)
The number of HWs with 95 %qn is maximal in August (8 cases), followed by July (6), lower in March (5) and lowest in May (4). In the same order is the ranking of (LSA SAF LST-T2m) values.
Seasonal behavior of temperature difference is in accordance to the seasonal SMA course.
Although the existence of SM deficit and much higher T2m in July, (LST-T2m) values are lower than these in March when the LC is still not developed and the insolation regime is different.
Surface-atmosphere coupling also increases the temperature anomaly on a seasonal scale.
In summer (Ts-T2m) increases in parallel with SM deficit.

25. G. Multilayer drought & Soil moisture deficit during HWs
The progression of soil moisture deficit in soil depth is accounted to analyze how it contributes to amplifying heat waves and was able to bring out different (LST-T2m) behaviors.
Widespread of drought to more deep soil layers leads to increase of (LST-T2m) up to C.
Latest drought occurs at 100 cm (4 Aug), (LST- T2m) accounts to 12.4 C, increasing up to 13 C (5 Sep) with increasing of SM deficit.
Very high negative correlation between (LST- T2m) difference and SMA100 cm.
16 June 2009
SMA is negative
at 20, 50 cm soil depth
10 June 2009
SMA is positive
at all soil depths
At positive SMA on 10 June, (LST-T2m) is low (6.9 C); at negative SMA for 20/50 cm soil depth on 16 June, (LST-T2m) increase up to 9.18 C.
Atmosphere and land surface interactions are based on an enhanced exchange of heat, moisture and momentum between the vegetation (including a deep root zone) and the overlying atmosphere.

26. H. HW-drought effects are linked to the local soil/microclimate
Land surface environment (temperature and moistening) during
95 %qn HWs, 2007, N Bulgaria, grass, Pleven (43.48; ), n = 22
Depending on weather and climate conditions, there might be difference in SMA/temperature environment during HWs in N/S Bulgaria.
north BG 2007
negative SMA
At the South (Ivailo) in 2007, SMA at 100 cm remains positive during all periods with HWs.
Temperature difference (LST-T2m) varies within more narrow limits C, being lower that than this of north BG (Pleven), where the temperature diapason is C.
south BG 2007
positive SMA

27. I. LSA SAF LST – SMA relation during HWs
Example: north Bulgaria
indeterminateness of LST at negative SMA
There is a strong correlation between Ts, derived by LSA SAF LST product and SMA:
The higher LST the lower SMA (including positive values)
This correlation is valid for:
each soil depth (20, 50, 100 cm) as well as
for single years and for long-term ( ) period
For extremely dry regimes when SMA is equal or below to water holding capacity, SMA can not longer be a leading factor for determining the LST.

28. I. LSA SAF LST – SMA relation during HWs
Example: south Bulgaria
SMA is higher than at North BG (Pleven).
Higher correlation (than at North) valid for whole soil depth (20, 50, 100 cm).
Specific:
At negative SMA, when AET and the functional link with atmosphere is interrupted, LST can not reflect exactly the severity of SMA depilation;
Less indeterminateness of LST at negative SMA.

29. J. Climate study of trends in SMA – (LST-T2m) relation during HWs
The indeterminateness of LST at negative SMA makes relevant to consider separately the average of negative SMA values from one side and the average of positive SMA values from the other. Analyses are performed for:
10 years HWs data set:
Yearly averaged values separately for June, July, August
Years with total HW duration (Tmax > 95%pn) more than one day are considered.
LST uses for the long term analyses
(LST-T2m) can be used as a proxy of quantified climatic SMA, being correlated in a similar way
for N-BG with more continental climatic influence
for S-BG with Mediterranean climatic influence.

30. J. Climate study of trends in SMA – LST relation during HWs
Strong negative correlations between summertime SMA and HWs LST temperatures.
For single stations there is even stronger correlation between mean LST / (LST-T2m) and SMA.
Mean negative SMA values correspond to higher LST and higher temperature difference (LST-T2m).

31. Concluding remarks
Quantification of HW-drought relations with focus on the role of soil moisture
Drier soils are acting to warm and dry the atmosphere and land surface at variety of climate regimes over southeastern Europe (Bulgaria). During HW, when SMA is exhausted and ET (derived by meteorological model) is prevented, LSA SAF LST values show definitely increasing trend.
There is a strong negative correlation between (LST-T2m) values and SM deficit (SMA) during summer June-August.
These relations could provide a set of methods for diagnosis and forecasts of land-atmosphere interactions in various climate projections.
The strong link between HWs and drought in E-Mediterranean suggests that we should treat them as different facets of the same phenomenon.

32. The focus is on the implementation of satellite information:
A physically motivated framework for studying drought is adopted
Satellite information is used in the context of the proposed conceptual scheme of drought
Use satellites to characterize HW-drought and link this to the variety of impacts
Drought monitoring with remote sensing
How satellite data for skin temperature can contribute to terrestrial drought assessment and to prediction of its effect (yield) ?
Persistence of droughts well predictable but onset is still a big challenge
Linking biomass burning and drought across Mediterranean.

33. Example # 1: Spatiotemporal distribution of agricultural drought
The (LST-T2m) Index is a meteorological product based on a set of thresholds, used as a measure of Soil Moisture Availability, approximate root zone soil moisture as a measure of agricultural drought risk (severity, duration).
Limitations: cloudy pixels

34. Satellites LST data in support to monitor water-energy-food nexus
Alert Risk of yield reduction
Second Law of Thermodynamics & Ecosystem functioning (Surface-Boundary approach in biothermodynamics, Florov, 1983; 1988; 2002).
(MSG LST-T2m) Index is used as a first proxy of climatic bioenergetic resources & related entropy production,  (Eq. 1)
Climatic (bioenergetic) resources and entropy production quantification:
Mean (MSG LST-T2m) Index during critical for yield formation period vs. mean yield ( ) of winter wheat* in Bulgaria
(1)
Mean wheat yield, kg/dka
Mean temperature difference (1200 LSA SAF LST-T2m), deg
Yield ranking:
Low
Moderate
High
Yield Forecast Moderate
Yield Assessed Moderate
/Ministry of Food and Agriculture/
Based on (LST-T2m) approximation
Wheat yield forecast for 2014 (kg/dk)
*NIMH agro database yield estimates.
Application example # 2: MSG LST data in support to assessment of climatic bioenergetic resources

35. Example # 3: Spatiotemporal distribution of drought related fire risk
27/08/2017 S-VIIRS 375 m
The (LST-T2m) Index is a meteorological product based on a set of thresholds, used as a measure of Soil Moisture Deficit, designating fuel dryness and susceptibility to burning.

36. Example: Ts from microwave SSM/I: Behavior during heat waves
Example # 4: Needs from reliable estimates of all-weather Ts
Example: Ts from microwave SSM/I: Behavior during heat waves
Morning Ts-Tair > 0
Heat waves across SE Europe in 2003 as characterized by (Ts –T2m) difference:
Morning-time (09:00 LT)
positive (as normal) and high temperature difference during whole season April-Sep
very high temperature difference of single cases are observed (further studies are needed for explanation)
Evening-time temperature difference (21:00 LT)
negative (as normal) temperature difference
steadily increasing from April to August due to the drought, and
becoming even positive, when is the peak of drought in 2003 (during August).
April
May
June
July
Aug
Sep
Evening Ts-Tair < 0
April
May
June
July
Aug
Sep
4th ESA DUE GlobTemperature User Consultation Meeting, 7-8 June 2016, Lisbon, Portugal

37. Decreasing SMA, valid for all soil depths (5, 20, 50, 100 cm), and
Example: Soil Moisture Availability & behaviour of Ts from microwave SSM/I
2003; day-time; selected months;
SMA site scale estimate from ‘SVAT_bg’ output
Increasing values of temperature difference (SSM/I Ts-T2m) are observed along with:
Decreasing SMA, valid for all soil depths (5, 20, 50, 100 cm), and
Valid for whole season (May, Aug, Sep)
Rainfall leads to increase of SMA that corresponds to decreasing (Ts-T2m) values

38. Acknowledgements
This study is funded by EUMETSAT, the European Organisation for the Exploitation of Meteorological Satellites in the frame of SALGEE Project TSMS has developed software for processing and visualisation of archive S-VIIRS 750 m data (in the frame of this SALGEE Project).
LSA SAF is acknowledged for providing data for LST product to fill the gaps for the test period.