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Forest landscape management for climate
change resilience in West and Central Africa
L. V. Verchot, K. Fernandes, D.J. Son...
Cameroon Policy responses
• Forest-Environment Sector Programme document
(FESP) does not mention CC
• 1st communication to...
Why climate adaptation is poorly reflected in
national development planning documents
• Poor data on adaptation options
• ...
Climatology
The PERSIANN dataset has the advantage of extending back to 1983
and is ¼ degree resolution. Combines satellit...
JJA trends of TRMM precipitation (left) and PERSIANN
precipitation (right). Period 2000-2014.
JJA trends in EVI (left), VH...
JJA-VHI JJA-EVI
JJA-TRMM
JJA-
PERSIANN
Correlation between the vegetation indices (columns) and precipitation datasets
(ro...
JJA-VHI JJA-EVI
MAMJJA
TRMM
MAMJJA-
PERSIANN
Changes in the northern sector are minimal, as JJA vegetation would respond t...
The point of the last 4 slides is to establish that
TRMM and PERSIANN data are consistent and that
trends found in TRMM ca...
Correlation between JJA VHI and PERSIANN MAMJJA precipitation
(a). Trends in VHI (b), PERSIANN JJA precipitation (c) and M...
MAMJJA precipitation trends. (a) PERSIANN 1985-2014, (b) GPCC 1985-
2014 and, (c) GPCC 1955-1984. Unit: mm/month per year....
MAMJJA SPI Trends 1955-1984 MAMJJA SPI Trends 1985-2014
-2,5
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
2,5
SPI 1955-1984
SPI 1985-2014...
Equatorial (western) Africa
Equatorial Africa for the
purpose of this analysis is the
area 5S-5N and 8E-30E.
Monthly mean ...
Climatology 1940-2014
Annual
SONJJA
MAMDJF
Precipitation Trends
(1940-2014)
Annual
MAMDJF
JJA SON
The trends shown
are 90% significant.
Units are mm/month
per year.
...
Timescales of variability- Domain 5S-
5N, 8E-30E
-20
-15
-10
-5
0
5
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25
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1942
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1946
1948
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1952
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19...
Timescales of variability- Domain 5S-5N, 8E-30E
Dry Seasons
Precipitation anomalies (mm/month) for DJF and JJA.
-30
-20
-1...
Timescales of variability- Domain 5S-5N, 8E-30E
Wet Seasons
-40
-30
-20
-10
0
10
20
30
40
50
1940
1942
1944
1946
1948
1950...
-20
-15
-10
-5
0
5
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20
25
1940
1942
1944
1946
1948
1950
1952
1954
1956
1958
1960
1962
1964
1966
1968
1970
1972
1974
1...
Correlation between unfiltered MAM Equatorial W. Africa precipitation
anomalies(grey bars in top figure) and MAM SSTs anom...
www.cifor.org
www.blog.cifor.org
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Verchot l 20150708_1500_upmc_jussieu_-_room_307

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Verchot l 20150708_1500_upmc_jussieu_-_room_307

  1. 1. Forest landscape management for climate change resilience in West and Central Africa L. V. Verchot, K. Fernandes, D.J. Sonwa, W. Baethgen, and M. Pinedo-Vasquez Our Common Future, Paris, July 2015
  2. 2. Cameroon Policy responses • Forest-Environment Sector Programme document (FESP) does not mention CC • 1st communication to the UNFCCC deals with sustainable forest management, but proposes no changes to meet CC challenge • Poverty reduction strategy paper (PRSP) does not mention CC
  3. 3. Why climate adaptation is poorly reflected in national development planning documents • Poor data on adaptation options • Limited awareness of adaptation among stakeholders and the population • Low staff capacity for planning, monitoring and evaluation • Lack of mechanisms for information sharing and management across sectors • Inadequate institutional capacity • Lack of commitment and incentives to enforce forest law • Lack of information about climate patterns
  4. 4. Climatology The PERSIANN dataset has the advantage of extending back to 1983 and is ¼ degree resolution. Combines satellite and gauge information. 50 70 90 110 130 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Central Africa domain Climatology from PERSIANN JJA DJF PERSIANN precipitation data in Central Africa 1983-2014. C. Africa domain averaged ppt (mm month-1)
  5. 5. JJA trends of TRMM precipitation (left) and PERSIANN precipitation (right). Period 2000-2014. JJA trends in EVI (left), VHI (right). Period 2000-2014. Vegetation indices (above) indicate a decrease in greenness since 2000. The precipitation trends (left) are much more modest and spotty.
  6. 6. JJA-VHI JJA-EVI JJA-TRMM JJA- PERSIANN Correlation between the vegetation indices (columns) and precipitation datasets (rows) for JJA. The correlations are calculated for the common period 2000-2014, constrained by EVI availability. As reported in Zhou 2014, the correlations between concurrent precipitation and Veg. indices are not high over the rainforest. Positive correlation between VHI and precipitation seem to perform better than EVI. The areas over the rainforest show a poorer relationship perhaps due to cloudiness.
  7. 7. JJA-VHI JJA-EVI MAMJJA TRMM MAMJJA- PERSIANN Changes in the northern sector are minimal, as JJA vegetation would respond to concurrent wet season precipitation (JJA) as previous months are very dry towards the Sahel. JJA: dry season in southern sector of the domain, Rainforest core is never really dry Correlations improve with a longer period (MAMJJA), especially in the south. Cumulative effect of precipitation over a 6 mo. is more relevant to veg response during JJA.
  8. 8. The point of the last 4 slides is to establish that TRMM and PERSIANN data are consistent and that trends found in TRMM can be found in PERSIANN. We want to use PERSIANN to see if the trends extend further back in time than what Zhou et al. (2014) found.
  9. 9. Correlation between JJA VHI and PERSIANN MAMJJA precipitation (a). Trends in VHI (b), PERSIANN JJA precipitation (c) and MAMJJA precipitation (d) for the period 1985-2014. Message: Long time-series are needed for trend analysis. The shorter period shown previously (2000-2014) shows decrease in vegetation indices and no consistent precipitation trend, whereas a longer time series show less significant vegetation trends, but better agreement with precipitation trends in the northern sector. (d)(c)(b)(a)
  10. 10. MAMJJA precipitation trends. (a) PERSIANN 1985-2014, (b) GPCC 1985- 2014 and, (c) GPCC 1955-1984. Unit: mm/month per year. (a) (b) (c) The plot (a) is the same as figure (d) in the previous slide. Plot b is for the same period, but the dataset is GPCC rain gauge only data. The spatial distribution of trends are consistent: patches of positive trends in the Sahel and negative in Central Africa. Plot (c) is GPCC MAMJJA trends but for last 30 years, showing opposite Sahelian trend.
  11. 11. MAMJJA SPI Trends 1955-1984 MAMJJA SPI Trends 1985-2014 -2,5 -2 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 SPI 1955-1984 SPI 1985-2014 Top: Same plots (b) and (c) from previous slide. Bottom: Bar plot is MAMJJA SPI calculated for the domain marked with a box in the map (5N-15N, 8E-34E).
  12. 12. Equatorial (western) Africa Equatorial Africa for the purpose of this analysis is the area 5S-5N and 8E-30E. Monthly mean precipitation for the domain 5S-5N and 8E-30E. Precipitation in the Congo follows a bimodal pattern with dry seasons (JJA and DJF) and 2 wet seasons (MAM and SON).
  13. 13. Climatology 1940-2014 Annual SONJJA MAMDJF
  14. 14. Precipitation Trends (1940-2014) Annual MAMDJF JJA SON The trends shown are 90% significant. Units are mm/month per year. Note the marked negative trend in MAM and DJF that reflect in the annual trend above.
  15. 15. Timescales of variability- Domain 5S- 5N, 8E-30E -20 -15 -10 -5 0 5 10 15 20 25 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Annual Trend DecV IntAnn Annual precipitation anomalies (mm/month). Note the predominance of dry years beginning in the 1970s and only recently recovering (with a vengeance)
  16. 16. Timescales of variability- Domain 5S-5N, 8E-30E Dry Seasons Precipitation anomalies (mm/month) for DJF and JJA. -30 -20 -10 0 10 20 30 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 DJF Trend DecV IntAnn -30 -20 -10 0 10 20 30 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 JJA Trend DecV IntAnn
  17. 17. Timescales of variability- Domain 5S-5N, 8E-30E Wet Seasons -40 -30 -20 -10 0 10 20 30 40 50 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 MAM Trend DecV IntAnn -40 -30 -20 -10 0 10 20 30 40 50 60 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 SON Trend DecV IntAnn Precipitation anomalies (mm/month) for MAM and SON.
  18. 18. -20 -15 -10 -5 0 5 10 15 20 25 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Annual Trend Correlation between unfiltered annual Equatorial W. Africa precipitation anomalies(grey bars in top figure) and annual SSTs anomalies. Studies have linked trends and variability of African climate to differential north-south ocean warming. This might be the cause of trend.
  19. 19. Correlation between unfiltered MAM Equatorial W. Africa precipitation anomalies(grey bars in top figure) and MAM SSTs anomalies. -40 -30 -20 -10 0 10 20 30 40 50 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 MAM Trend DecV IntAnn
  20. 20. www.cifor.org www.blog.cifor.org

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